Effects of contrarians in the minority game

NASA Astrophysics Data System (ADS)

Zhong, Li-Xin; Zheng, Da-Fang; Zheng, Bo; Hui, P. M.

2005-08-01

We study the effects of the presence of contrarians in an agent-based model of competing populations. Contrarians are common in societies. These contrarians are agents who deliberately prefer to hold an opinion that is contrary to the prevailing idea of the commons or normal agents. Contrarians are introduced within the context of the minority game (MG), which is a binary model for an evolving and adaptive population of agents competing for a limited resource. The average success rate among the agents is found to have a nonmonotonic dependence on the fraction ac of contrarians. For small ac , the contrarians systematically outperform the normal agents by avoiding the crowd effect and enhance the overall success rate. For high ac , the antipersistent nature of the MG is disturbed and the few normal agents outperform the contrarians. Qualitative discussion and analytic results for the small ac and high ac regimes are presented, and the crossover behavior between the two regimes is discussed.

Forgetfulness can help you win games.

PubMed

Burridge, James; Gao, Yu; Mao, Yong

2015-09-01

We present a simple game model where agents with different memory lengths compete for finite resources. We show by simulation and analytically that an instability exists at a critical memory length, and as a result, different memory lengths can compete and coexist in a dynamical equilibrium. Our analytical formulation makes a connection to statistical urn models, and we show that temperature is mirrored by the agent's memory. Our simple model of memory may be incorporated into other game models with implications that we briefly discuss.

Using an agent-based model to simulate children’s active travel to school

PubMed Central

2013-01-01

Background Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children’s active travel to school. Methods An agent-based model was developed to simulate children’s school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. Results To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Conclusions Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school. PMID:23705953

Using an agent-based model to simulate children's active travel to school.

PubMed

Yang, Yong; Diez-Roux, Ana V

2013-05-26

Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children's active travel to school. An agent-based model was developed to simulate children's school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school.

Epidemic modeling with discrete-space scheduled walkers: extensions and research opportunities

PubMed Central

2009-01-01

Background This exploratory paper outlines an epidemic simulator built on an agent-based, data-driven model of the spread of a disease within an urban environment. An intent of the model is to provide insight into how a disease may reach a tipping point, spreading to an epidemic of uncontrollable proportions. Methods As a complement to analytical methods, simulation is arguably an effective means of gaining a better understanding of system-level disease dynamics within a population and offers greater utility in its modeling capabilities. Our investigation is based on this conjecture, supported by data-driven models that are reasonable, realistic and practical, in an attempt to demonstrate their efficacy in studying system-wide epidemic phenomena. An agent-based model (ABM) offers considerable flexibility in extending the study of the phenomena before, during and after an outbreak or catastrophe. Results An agent-based model was developed based on a paradigm of a 'discrete-space scheduled walker' (DSSW), modeling a medium-sized North American City of 650,000 discrete agents, built upon a conceptual framework of statistical reasoning (law of large numbers, statistical mechanics) as well as a correct-by-construction bias. The model addresses where, who, when and what elements, corresponding to network topography and agent characteristics, behaviours, and interactions upon that topography. The DSSW-ABM has an interface and associated scripts that allow for a variety of what-if scenarios modeling disease spread throughout the population, and for data to be collected and displayed via a web browser. Conclusion This exploratory paper also presents several research opportunities for exploiting data sources of a non-obvious and disparate nature for the purposes of epidemic modeling. There is an increasing amount and variety of data that will continue to contribute to the accuracy of agent-based models and improve their utility in modeling disease spread. The model developed here is well suited to diseases where there is not a predisposition for contraction within the population. One of the advantages of agent-based modeling is the ability to set up a rare event and develop policy as to how one may mitigate damages arising from it. PMID:19922684

Epidemic modeling with discrete-space scheduled walkers: extensions and research opportunities.

PubMed

Borkowski, Maciej; Podaima, Blake W; McLeod, Robert D

2009-11-18

This exploratory paper outlines an epidemic simulator built on an agent-based, data-driven model of the spread of a disease within an urban environment. An intent of the model is to provide insight into how a disease may reach a tipping point, spreading to an epidemic of uncontrollable proportions. As a complement to analytical methods, simulation is arguably an effective means of gaining a better understanding of system-level disease dynamics within a population and offers greater utility in its modeling capabilities. Our investigation is based on this conjecture, supported by data-driven models that are reasonable, realistic and practical, in an attempt to demonstrate their efficacy in studying system-wide epidemic phenomena. An agent-based model (ABM) offers considerable flexibility in extending the study of the phenomena before, during and after an outbreak or catastrophe. An agent-based model was developed based on a paradigm of a 'discrete-space scheduled walker' (DSSW), modeling a medium-sized North American City of 650,000 discrete agents, built upon a conceptual framework of statistical reasoning (law of large numbers, statistical mechanics) as well as a correct-by-construction bias. The model addresses where, who, when and what elements, corresponding to network topography and agent characteristics, behaviours, and interactions upon that topography. The DSSW-ABM has an interface and associated scripts that allow for a variety of what-if scenarios modeling disease spread throughout the population, and for data to be collected and displayed via a web browser. This exploratory paper also presents several research opportunities for exploiting data sources of a non-obvious and disparate nature for the purposes of epidemic modeling. There is an increasing amount and variety of data that will continue to contribute to the accuracy of agent-based models and improve their utility in modeling disease spread. The model developed here is well suited to diseases where there is not a predisposition for contraction within the population. One of the advantages of agent-based modeling is the ability to set up a rare event and develop policy as to how one may mitigate damages arising from it.

Cooperative peer-to-peer multiagent-based systems

NASA Astrophysics Data System (ADS)

Caram, L. F.; Caiafa, C. F.; Ausloos, M.; Proto, A. N.

2015-08-01

A multiagent based model for a system of cooperative agents aiming at growth is proposed. This is based on a set of generalized Verhulst-Lotka-Volterra differential equations. In this study, strong cooperation is allowed among agents having similar sizes, and weak cooperation if agents have markedly different "sizes", thus establishing a peer-to-peer modulated interaction scheme. A rigorous analysis of the stable configurations is presented first examining the fixed points of the system, next determining their stability as a function of the model parameters. It is found that the agents are self-organizing into clusters. Furthermore, it is demonstrated that, depending on parameter values, multiple stable configurations can coexist. It occurs that only one of them always emerges with probability close to one, because its associated attractor dominates over the rest. This is shown through numerical integrations and simulations, after analytic developments. In contrast to the competitive case, agents are able to increase their capacity beyond the no-interaction case limit. In other words, when some collaborative partnership among a relatively small number of partners takes place, all agents act in good faith prioritizing the common good, when receiving a mutual benefit allowing them to surpass their capacity.

Cooperative peer-to-peer multiagent-based systems.

PubMed

Caram, L F; Caiafa, C F; Ausloos, M; Proto, A N

2015-08-01

A multiagent based model for a system of cooperative agents aiming at growth is proposed. This is based on a set of generalized Verhulst-Lotka-Volterra differential equations. In this study, strong cooperation is allowed among agents having similar sizes, and weak cooperation if agents have markedly different "sizes", thus establishing a peer-to-peer modulated interaction scheme. A rigorous analysis of the stable configurations is presented first examining the fixed points of the system, next determining their stability as a function of the model parameters. It is found that the agents are self-organizing into clusters. Furthermore, it is demonstrated that, depending on parameter values, multiple stable configurations can coexist. It occurs that only one of them always emerges with probability close to one, because its associated attractor dominates over the rest. This is shown through numerical integrations and simulations, after analytic developments. In contrast to the competitive case, agents are able to increase their capacity beyond the no-interaction case limit. In other words, when some collaborative partnership among a relatively small number of partners takes place, all agents act in good faith prioritizing the common good, when receiving a mutual benefit allowing them to surpass their capacity.

Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

PubMed

Frantz, Terrill L

2012-01-01

This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities. Copyright © 2012 S. Karger AG, Basel.

Symmetry-based reciprocity: evolutionary constraints on a proximate mechanism

PubMed Central

Campennì, Marco

2016-01-01

Background. While the evolution of reciprocal cooperation has attracted an enormous attention, the proximate mechanisms underlying the ability of animals to cooperate reciprocally are comparatively neglected. Symmetry-based reciprocity is a hypothetical proximate mechanism that has been suggested to be widespread among cognitively unsophisticated animals. Methods. We developed two agent-based models of symmetry-based reciprocity (one relying on an arbitrary tag and the other on interindividual proximity) and tested their ability both to reproduce significant emergent features of cooperation in group living animals and to promote the evolution of cooperation. Results. Populations formed by agents adopting symmetry-based reciprocity showed differentiated “social relationships” and a positive correlation between cooperation given and received: two common aspects of animal cooperation. However, when reproduction and selection across multiple generations were added to the models, agents adopting symmetry-based reciprocity were outcompeted by selfish agents that never cooperated. Discussion. In order to evolve, hypothetical proximate mechanisms must be able to stand competition from alternative strategies. While the results of our simulations require confirmation using analytical methods, we provisionally suggest symmetry-based reciprocity is to be abandoned as a possible proximate mechanism underlying the ability of animals to reciprocate cooperative interactions. PMID:26998412

Symmetry-based reciprocity: evolutionary constraints on a proximate mechanism.

PubMed

Campennì, Marco; Schino, Gabriele

2016-01-01

Background. While the evolution of reciprocal cooperation has attracted an enormous attention, the proximate mechanisms underlying the ability of animals to cooperate reciprocally are comparatively neglected. Symmetry-based reciprocity is a hypothetical proximate mechanism that has been suggested to be widespread among cognitively unsophisticated animals. Methods. We developed two agent-based models of symmetry-based reciprocity (one relying on an arbitrary tag and the other on interindividual proximity) and tested their ability both to reproduce significant emergent features of cooperation in group living animals and to promote the evolution of cooperation. Results. Populations formed by agents adopting symmetry-based reciprocity showed differentiated "social relationships" and a positive correlation between cooperation given and received: two common aspects of animal cooperation. However, when reproduction and selection across multiple generations were added to the models, agents adopting symmetry-based reciprocity were outcompeted by selfish agents that never cooperated. Discussion. In order to evolve, hypothetical proximate mechanisms must be able to stand competition from alternative strategies. While the results of our simulations require confirmation using analytical methods, we provisionally suggest symmetry-based reciprocity is to be abandoned as a possible proximate mechanism underlying the ability of animals to reciprocate cooperative interactions.

The Hamming distance in the minority game

NASA Astrophysics Data System (ADS)

D'hulst, R.; Rodgers, G. J.

1999-08-01

We investigate different versions of the minority game, a toy model for agents buying and selling a commodity. The Hamming distance between the strategies used by agents to make decisions is introduced as an analytical tool to determine several properties of these models. The success rate of the agents in an adaptive version of the game is compared with the rate from a stochastic version. It is shown numerically and analytically that the adaptive process is inefficient, increasing the success rate of the unused strategies while decreasing the success rate of the strategies used by the agents. The agents do not do as well as if they were forced to use only one strategy permanently. A version of the game in which the agents strategies evolve is also analysed using the notion of distance. The agents evolve into a state in which they are all using one strategy, which is again the state that yields the maximum success rate.

Is the person-situation debate important for agent-based modeling and vice-versa?

PubMed

Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał

2014-01-01

Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not. Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature. This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments.

Evolvable mathematical models: A new artificial Intelligence paradigm

NASA Astrophysics Data System (ADS)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

NASA Astrophysics Data System (ADS)

Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

2009-02-01

We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

Active Brownian agents with concentration-dependent chemotactic sensitivity.

PubMed

Meyer, Marcel; Schimansky-Geier, Lutz; Romanczuk, Pawel

2014-02-01

We study a biologically motivated model of overdamped, autochemotactic Brownian agents with concentration-dependent chemotactic sensitivity. The agents in our model move stochastically and produce a chemical ligand at their current position. The ligand concentration obeys a reaction-diffusion equation and acts as a chemoattractant for the agents, which bias their motion towards higher concentrations of the dynamically altered chemical field. We explore the impact of concentration-dependent response to chemoattractant gradients on large-scale pattern formation, by deriving a coarse-grained macroscopic description of the individual-based model, and compare the conditions for emergence of inhomogeneous solutions for different variants of the chemotactic sensitivity. We focus primarily on the so-called receptor-law sensitivity, which models a nonlinear decrease of chemotactic sensitivity with increasing ligand concentration. Our results reveal qualitative differences between the receptor law, the constant chemotactic response, and the so-called log law, with respect to stability of the homogeneous solution, as well as the emergence of different patterns (labyrinthine structures, clusters, and bubbles) via spinodal decomposition or nucleation. We discuss two limiting cases, where the model can be reduced to the dynamics of single species: (I) the agent density governed by a density-dependent effective diffusion coefficient and (II) the ligand field with an effective bistable, time-dependent reaction rate. In the end, we turn to single clusters of agents, studying domain growth and determining mean characteristics of the stationary inhomogeneous state. Analytical results are confirmed and extended by large-scale GPU simulations of the individual based model.

Consumer Search, Rationing Rules, and the Consequence for Competition

NASA Astrophysics Data System (ADS)

Ruebeck, Christopher S.

Firms' conjectures about demand are consequential in oligopoly games. Through agent-based modeling of consumers' search for products, we can study the rationing of demand between capacity-constrained firms offering homogeneous products and explore the robustness of analytically solvable models' results. After algorithmically formalizing short-run search behavior rather than assuming a long-run average, this study predicts stronger competition in a two-stage capacity-price game.

Incorporating inertia into multiagent systems

NASA Astrophysics Data System (ADS)

Man, W. C.; Chau, H. F.

2006-03-01

We consider a model that demonstrates the crucial role of inertia and stickiness in multiagent systems, based on the minority game. The inertia of an agent is introduced into the game model by allowing agents to apply hypothesis testing when choosing their best strategies, thereby reducing their reactivity toward changes in the environment. We find by extensive numerical simulations that our game shows a remarkable improvement of global cooperation throughout the whole phase space. In other words, the maladaptation behavior due to over-reaction of agents is removed. These agents are also shown to be advantageous over the standard ones, which are sometimes too sensitive to attain a fair success rate. We also calculate analytically the minimum amount of inertia needed to achieve the above improvement. Our calculation is consistent with the numerical simulation results. Finally, we review some related works in the field that show similar behaviors and compare them to our work.

Properties of interaction networks underlying the minority game.

PubMed

Caridi, Inés

2014-11-01

The minority game is a well-known agent-based model with no explicit interaction among its agents. However, it is known that they interact through the global magnitudes of the model and through their strategies. In this work we have attempted to formalize the implicit interactions among minority game agents as if they were links on a complex network. We have defined the link between two agents by quantifying the similarity between them. This link definition is based on the information of the instance of the game (the set of strategies assigned to each agent at the beginning) without any dynamic information on the game and brings about a static, unweighed and undirected network. We have analyzed the structure of the resulting network for different parameters, such as the number of agents (N) and the agent's capacity to process information (m), always taking into account games with two strategies per agent. In the region of crowd effects of the model, the resulting networks structure is a small-world network, whereas in the region where the behavior of the minority game is the same as in a game of random decisions, networks become a random network of Erdos-Renyi. The transition between these two types of networks is slow, without any peculiar feature of the network in the region of the coordination among agents. Finally, we have studied the resulting static networks for the full strategy minority game model, a maximal instance of the minority game in which all possible agents take part in the game. We have explicitly calculated the degree distribution of the full strategy minority game network and, on the basis of this analytical result, we have estimated the degree distribution of the minority game network, which is in accordance with computational results.

Adaptive behaviors in multi-agent source localization using passive sensing.

PubMed

Shaukat, Mansoor; Chitre, Mandar

2016-12-01

In this paper, the role of adaptive group cohesion in a cooperative multi-agent source localization problem is investigated. A distributed source localization algorithm is presented for a homogeneous team of simple agents. An agent uses a single sensor to sense the gradient and two sensors to sense its neighbors. The algorithm is a set of individualistic and social behaviors where the individualistic behavior is as simple as an agent keeping its previous heading and is not self-sufficient in localizing the source. Source localization is achieved as an emergent property through agent's adaptive interactions with the neighbors and the environment. Given a single agent is incapable of localizing the source, maintaining team connectivity at all times is crucial. Two simple temporal sampling behaviors, intensity-based-adaptation and connectivity-based-adaptation, ensure an efficient localization strategy with minimal agent breakaways. The agent behaviors are simultaneously optimized using a two phase evolutionary optimization process. The optimized behaviors are estimated with analytical models and the resulting collective behavior is validated against the agent's sensor and actuator noise, strong multi-path interference due to environment variability, initialization distance sensitivity and loss of source signal.

Value of the distant future: Model-independent results

NASA Astrophysics Data System (ADS)

Katz, Yuri A.

2017-01-01

This paper shows that the model-independent account of correlations in an interest rate process or a log-consumption growth process leads to declining long-term tails of discount curves. Under the assumption of an exponentially decaying memory in fluctuations of risk-free real interest rates, I derive the analytical expression for an apt value of the long run discount factor and provide a detailed comparison of the obtained result with the outcome of the benchmark risk-free interest rate models. Utilizing the standard consumption-based model with an isoelastic power utility of the representative economic agent, I derive the non-Markovian generalization of the Ramsey discounting formula. Obtained analytical results allowing simple calibration, may augment the rigorous cost-benefit and regulatory impact analysis of long-term environmental and infrastructure projects.

Laplace transform analysis of a multiplicative asset transfer model

NASA Astrophysics Data System (ADS)

Sokolov, Andrey; Melatos, Andrew; Kieu, Tien

2010-07-01

We analyze a simple asset transfer model in which the transfer amount is a fixed fraction f of the giver’s wealth. The model is analyzed in a new way by Laplace transforming the master equation, solving it analytically and numerically for the steady-state distribution, and exploring the solutions for various values of f∈(0,1). The Laplace transform analysis is superior to agent-based simulations as it does not depend on the number of agents, enabling us to study entropy and inequality in regimes that are costly to address with simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g. non-monotonic) measure of disorder in a multiplicative asset transfer system and suggest an asymmetric stochastic process that is equivalent to the asset transfer model.

Affinity extraction of emerging contaminants from water based on bovine serum albumin as a binding agent.

PubMed

Papastavros, Efthimia; Remmers, Rachael A; Snow, Daniel D; Cassada, David A; Hage, David S

2018-03-01

Affinity sorbents using bovine serum albumin as a binding agent were developed and tested for the extraction of environmental contaminants from water. Computer simulations based on a countercurrent distribution model were also used to study the behavior of these sorbents. Several model drugs, pesticides, and hormones of interest as emerging contaminants were considered in this work, with carbamazepine being used as a representative analyte when coupling the albumin column on-line with liquid chromatography and tandem mass spectrometry. The albumin column was found to be capable of extracting carbamazepine from aqueous solutions that contained trace levels of this analyte. Further studies of the bovine serum albumin sorbent indicated that it had higher retention under aqueous conditions than a traditional C 18 support for most of the tested emerging contaminants. Potential advantages of using these protein-based sorbents included the low cost of bovine serum albumin and its ability to bind to a relatively wide range of drugs and related compounds. It was also shown how simulations could be used to describe the elution behavior of the model compounds on the bovine serum albumin sorbents as an aid in optimizing the retention and selectivity of these supports for use with liquid chromatography or methods such as liquid chromatography with tandem mass spectrometry. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optical detection of chemical warfare agents and toxic industrial chemicals

NASA Astrophysics Data System (ADS)

Webber, Michael E.; Pushkarsky, Michael B.; Patel, C. Kumar N.

2004-12-01

We present an analytical model evaluating the suitability of optical absorption based spectroscopic techniques for detection of chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) in ambient air. The sensor performance is modeled by simulating absorption spectra of a sample containing both the target and multitude of interfering species as well as an appropriate stochastic noise and determining the target concentrations from the simulated spectra via a least square fit (LSF) algorithm. The distribution of the LSF target concentrations determines the sensor sensitivity, probability of false positives (PFP) and probability of false negatives (PFN). The model was applied to CO2 laser based photoacosutic (L-PAS) CWA sensor and predicted single digit ppb sensitivity with very low PFP rates in the presence of significant amount of interferences. This approach will be useful for assessing sensor performance by developers and users alike; it also provides methodology for inter-comparison of different sensing technologies.

Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

NASA Technical Reports Server (NTRS)

Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

2012-01-01

Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

Dendritic growth model of multilevel marketing

NASA Astrophysics Data System (ADS)

Pang, James Christopher S.; Monterola, Christopher P.

2017-02-01

Biologically inspired dendritic network growth is utilized to model the evolving connections of a multilevel marketing (MLM) enterprise. Starting from agents at random spatial locations, a network is formed by minimizing a distance cost function controlled by a parameter, termed the balancing factor bf, that weighs the wiring and the path length costs of connection. The paradigm is compared to an actual MLM membership data and is shown to be successful in statistically capturing the membership distribution, better than the previously reported agent based preferential attachment or analytic branching process models. Moreover, it recovers the known empirical statistics of previously studied MLM, specifically: (i) a membership distribution characterized by the existence of peak levels indicating limited growth, and (ii) an income distribution obeying the 80 - 20 Pareto principle. Extensive types of income distributions from uniform to Pareto to a "winner-take-all" kind are also modeled by varying bf. Finally, the robustness of our dendritic growth paradigm to random agent removals is explored and its implications to MLM income distributions are discussed.

Dynamics of three-agent games

NASA Astrophysics Data System (ADS)

Mungan, Muhittin; Rador, Tonguç

2008-02-01

We study the dynamics and resulting score distribution of three-agent games where after each competition a single agent wins and scores a point. A single competition is described by a triplet of numbers p, t and q denoting the probabilities that the team with the highest, middle or lowest accumulated score wins. The three-agent game can be regarded as a social model where a player can be favored or disfavored for advancement, based on his/her accumulated score. We study the full family of solutions in the regime, where the number of agents and competitions is large, which can be regarded as a hydrodynamic limit. Depending on the parameter values (p, q, t), we find six qualitatively different asymptotic score distributions and we provide a qualitative explanation of these results. We also compare our analytical results against numerical simulations of the microscopic model and find these to be in excellent agreement. It is possible to decide the outcome of a three-agent game through a mini-tournament of two-agent competitions among the participating players and it turns out that the resulting possible score distributions are a subset of those obtained for the general three-agent games. We discuss how one can add a steady and democratic decline rate to the model and present a simple geometric construction that allows one to obtain the score evolution equations for n-agent games.

Competition of information channels in the spreading of innovations

NASA Astrophysics Data System (ADS)

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Competition of information channels in the spreading of innovations.

PubMed

Kocsis, Gergely; Kun, Ferenc

2011-08-01

We study the spreading of information on technological developments in socioeconomic systems where the social contacts of agents are represented by a network of connections. In the model, agents get informed about the existence and advantages of new innovations through advertising activities of producers, which are then followed by an interagent information transfer. Computer simulations revealed that varying the strength of external driving and of interagent coupling, furthermore, the topology of social contacts, the model presents a complex behavior with interesting novel features: On the macrolevel the system exhibits logistic behavior typical for the diffusion of innovations. The time evolution can be described analytically by an integral equation that captures the nucleation and growth of clusters of informed agents. On the microlevel, small clusters are found to be compact with a crossover to fractal structures with increasing size. The distribution of cluster sizes has a power-law behavior with a crossover to a higher exponent when long-range social contacts are present in the system. Based on computer simulations we construct an approximate phase diagram of the model on a regular square lattice of agents.

Mass diffusion coefficient measurement for vitreous humor using FEM and MRI

NASA Astrophysics Data System (ADS)

Rattanakijsuntorn, Komsan; Penkova, Anita; Sadha, Satwindar S.

2018-01-01

In early studies, the ‘contour method’ for determining the diffusion coefficient of the vitreous humor was developed. This technique relied on careful injection of an MRI contrast agent (surrogate drug) into the vitreous humor of fresh bovine eyes, and tracking the contours of the contrast agent in time. In addition, an analytical solution was developed for the theoretical contours built on point source model for the injected surrogate drug. The match between theoretical and experimental contours as a least square fit, while floating the diffusion coefficient, led to the value of the diffusion coefficient. This method had its limitation that the initial injection of the surrogate had to be spherical or ellipsoidal because of the analytical result based on the point-source model. With a new finite element model for the analysis in this study, the technique is much less restrictive and handles irregular shapes of the initial bolus. The fresh bovine eyes were used for drug diffusion study in the vitreous and three contrast agents of different molecular masses: gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA, 938 Da), non-ionic gadoteridol (Prohance, 559 Da), and bovine albumin conjugated with gadolinium (Galbumin, 74 kDa) were used as drug surrogates to visualize the diffusion process by MRI. The 3D finite element model was developed to determine the diffusion coefficients of these surrogates with the images from MRI. This method can be used for other types of bioporous media provided the concentration profile can be visualized (by methods such as MRI or fluorescence).

Integrating GIS and ABM to Explore Spatiotemporal Dynamics

NASA Astrophysics Data System (ADS)

Sun, M.; Jiang, Y.; Yang, C.

2013-12-01

Agent-based modeling as a methodology for the bottom-up exploration with the account of adaptive behavior and heterogeneity of system components can help discover the development and pattern of the complex social and environmental system. However, ABM is a computationally intensive process especially when the number of system components becomes large and the agent-agent/agent-environmental interaction is modeled very complex. Most of traditional ABM frameworks developed based on CPU do not have a satisfying computing capacity. To address the problem and as the emergence of advanced techniques, GPU computing with CUDA can provide powerful parallel structure to enable the complex simulation of spatiotemporal dynamics. In this study, we first develop a GPU-based ABM system. Secondly, in order to visualize the dynamics generated from the movement of agent and the change of agent/environmental attributes during the simulation, we integrate GIS into the ABM system. Advanced geovisualization technologies can be utilized for representing the spatiotemporal change events, such as proper 2D/3D maps with state-of-the-art symbols, space-time cube and multiple layers each of which presents pattern in one time-stamp, etc. Thirdly, visual analytics which include interactive tools (e.g. grouping, filtering, linking, etc.) is included in our ABM-GIS system to help users conduct real-time data exploration during the progress of simulation. Analysis like flow analysis and spatial cluster analysis can be integrated according to the geographical problem we want to explore.

On the emergence of an ‘intention field’ for socially cohesive agents

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Borghesi, Christian; Jensen, Pablo

2014-03-01

We argue that when a social convergence mechanism exists and is strong enough, one should expect the emergence of a well-defined ‘field’, i.e. a slowly evolving, local quantity around which individual attributes fluctuate in a finite range. This condensation phenomenon is well illustrated by the Deffuant-Weisbuch opinion model for which we provide a natural extension to allow for spatial heterogeneities. We show analytically and numerically that the resulting dynamics of the emergent field is a noisy diffusion equation that has a slow dynamics. This random diffusion equation reproduces the long-ranged, logarithmic decrease of the correlation of spatial voting patterns empirically found in Borghesi and Bouchaud (2010 Eur. Phys. J. B 75 395) and Borghesi et al (2012 PLoS One 7 e36289). Interestingly enough, we find that when the social cohesion mechanism becomes too weak, cultural cohesion breaks down completely, in the sense that the distribution of intentions/opinions becomes infinitely broad. No emerging field exists in this case. All these analytical findings are confirmed by numerical simulations of an agent-based model.

Parallel Agent-Based Simulations on Clusters of GPUs and Multi-Core Processors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaby, Brandon G; Perumalla, Kalyan S; Seal, Sudip K

2010-01-01

An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Messagemore » Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.« less

Dynamical systems approach to the study of a sociophysics agent-based model

NASA Astrophysics Data System (ADS)

Timpanaro, André M.; Prado, Carmen P. C.

2011-03-01

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2] (where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: ησ = ∑ σ' = 1Mησησ'(ησρσ'→σ-σ'ρσ→σ'). Where hs is the proportion of agents with opinion (spin) σ', M is the number of opinions and σ'→σ' is the probability weight for an agent with opinion σ being convinced by another agent with opinion σ'. We made Monte Carlo simulations of the model in a complex network (using Barabási-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.

Estimation of a simple agent-based model of financial markets: An application to Australian stock and foreign exchange data

NASA Astrophysics Data System (ADS)

Alfarano, Simone; Lux, Thomas; Wagner, Friedrich

2006-10-01

Following Alfarano et al. [Estimation of agent-based models: the case of an asymmetric herding model, Comput. Econ. 26 (2005) 19-49; Excess volatility and herding in an artificial financial market: analytical approach and estimation, in: W. Franz, H. Ramser, M. Stadler (Eds.), Funktionsfähigkeit und Stabilität von Finanzmärkten, Mohr Siebeck, Tübingen, 2005, pp. 241-254], we consider a simple agent-based model of a highly stylized financial market. The model takes Kirman's ant process [A. Kirman, Epidemics of opinion and speculative bubbles in financial markets, in: M.P. Taylor (Ed.), Money and Financial Markets, Blackwell, Cambridge, 1991, pp. 354-368; A. Kirman, Ants, rationality, and recruitment, Q. J. Econ. 108 (1993) 137-156] of mimetic contagion as its starting point, but allows for asymmetry in the attractiveness of both groups. Embedding the contagion process into a standard asset-pricing framework, and identifying the abstract groups of the herding model as chartists and fundamentalist traders, a market with periodic bubbles and bursts is obtained. Taking stock of the availability of a closed-form solution for the stationary distribution of returns for this model, we can estimate its parameters via maximum likelihood. Expanding our earlier work, this paper presents pertinent estimates for the Australian dollar/US dollar exchange rate and the Australian stock market index. As it turns out, our model indicates dominance of fundamentalist behavior in both the stock and foreign exchange market.

Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

PubMed

Sakamoto, Takuto

2016-01-01

Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery

PubMed Central

Sakamoto, Takuto

2016-01-01

Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level. PMID:26963526

Analytical Modelling of the Spread of Disease in Confined and Crowded Spaces

NASA Astrophysics Data System (ADS)

Goscé, Lara; Barton, David A. W.; Johansson, Anders

2014-05-01

Since 1927 and until recently, most models describing the spread of disease have been of compartmental type, based on the assumption that populations are homogeneous and well-mixed. Recent models have utilised agent-based models and complex networks to explicitly study heterogeneous interaction patterns, but this leads to an increasing computational complexity. Compartmental models are appealing because of their simplicity, but their parameters, especially the transmission rate, are complex and depend on a number of factors, which makes it hard to predict how a change of a single environmental, demographic, or epidemiological factor will affect the population. Therefore, in this contribution we propose a middle ground, utilising crowd-behaviour research to improve compartmental models in crowded situations. We show how both the rate of infection as well as the walking speed depend on the local crowd density around an infected individual. The combined effect is that the rate of infection at a population scale has an analytically tractable non-linear dependency on crowd density. We model the spread of a hypothetical disease in a corridor and compare our new model with a typical compartmental model, which highlights the regime in which current models may not produce credible results.

The Hunt Opinion Model-An Agent Based Approach to Recurring Fashion Cycles.

PubMed

Apriasz, Rafał; Krueger, Tyll; Marcjasz, Grzegorz; Sznajd-Weron, Katarzyna

2016-01-01

We study a simple agent-based model of the recurring fashion cycles in the society that consists of two interacting communities: "snobs" and "followers" (or "opinion hunters", hence the name of the model). Followers conform to all other individuals, whereas snobs conform only to their own group and anticonform to the other. The model allows to examine the role of the social structure, i.e. the influence of the number of inter-links between the two communities, as well as the role of the stability of links. The latter is accomplished by considering two versions of the same model-quenched (parameterized by fraction L of fixed inter-links) and annealed (parameterized by probability p that a given inter-link exists). Using Monte Carlo simulations and analytical treatment (the latter only for the annealed model), we show that there is a critical fraction of inter-links, above which recurring cycles occur. For p ≤ 0.5 we derive a relation between parameters L and p that allows to compare both models and show that the critical value of inter-connections, p*, is the same for both versions of the model (annealed and quenched) but the period of a fashion cycle is shorter for the quenched model. Near the critical point, the cycles are irregular and a change of fashion is difficult to predict. For the annealed model we also provide a deeper theoretical analysis. We conjecture on topological grounds that the so-called saddle node heteroclinic bifurcation appears at p*. For p ≥ 0.5 we show analytically the existence of the second critical value of p, for which the system undergoes Hopf's bifurcation.

Experimental And Numerical Evaluation Of Gaseous Agents For Suppressing Cup-Burner Flames In Low Gravity

NASA Technical Reports Server (NTRS)

Takahashi, Fumiaki; Linteris, Gregory T.; Katta, Viswanath R.

2003-01-01

Longer duration missions to the moon, to Mars, and on the International Space Station (ISS) increase the likelihood of accidental fires. NASA's fire safety program for human-crewed space flight is based largely on removing ignition sources and controlling the flammability of the material on-board. There is ongoing research to improve the flammability characterization of materials in low gravity; however, very little research has been conducted on fire suppression in the low-gravity environment. Although the existing suppression systems aboard the Space Shuttle (halon 1301, CF3Br) and the ISS (CO2 or water-based form) may continue to be used, alternative effective agents or techniques are desirable for long-duration missions. The goal of the present investigation is to: (1) understand the physical and chemical processes of fire suppression in various gravity and O2 levels simulating spacecraft, Mars, and moon missions; (2) provide rigorous testing of analytical models, which include detailed combustion-suppression chemistry and radiation sub-models, so that the model can be used to interpret (and predict) the suppression behavior in low gravity; and (3) provide basic research results useful for advances in space fire safety technology, including new fire-extinguishing agents and approaches.

Modeling Analyte Transport and Capture in Porous Bead Sensors

PubMed Central

Chou, Jie; Lennart, Alexis; Wong, Jorge; Ali, Mehnaaz F.; Floriano, Pierre N.; Christodoulides, Nicolaos; Camp, James; McDevitt, John T.

2013-01-01

Porous agarose microbeads, with high surface to volume ratios and high binding densities, are attracting attention as highly sensitive, affordable sensor elements for a variety of high performance bioassays. While such polymer microspheres have been extensively studied and reported on previously and are now moving into real-world clinical practice, very little work has been completed to date to model the convection, diffusion, and binding kinetics of soluble reagents captured within such fibrous networks. Here, we report the development of a three-dimensional computational model and provide the initial evidence for its agreement with experimental outcomes derived from the capture and detection of representative protein and genetic biomolecules in 290μm porous beads. We compare this model to antibody-mediated capture of C-reactive protein and bovine serum albumin, along with hybridization of oligonucleotide sequences to DNA probes. These results suggest that due to the porous interior of the agarose bead, internal analyte transport is both diffusion- and convection-based, and regardless of the nature of analyte, the bead interiors reveal an interesting trickle of convection-driven internal flow. Based on this model, the internal to external flow rate ratio is found to be in the range of 1:3100 to 1:170 for beads with agarose concentration ranging from 0.5% to 8% for the sensor ensembles here studied. Further, both model and experimental evidence suggest that binding kinetics strongly affect analyte distribution of captured reagents within the beads. These findings reveal that high association constants create a steep moving boundary in which unbound analytes are held back at the periphery of the bead sensor. Low association constants create a more shallow moving boundary in which unbound analytes diffuse further into the bead before binding. These models agree with experimental evidence and thus serve as a new tool set for the study of bio-agent transport processes within a new class of medical microdevices. PMID:22250703

The Hunt Opinion Model—An Agent Based Approach to Recurring Fashion Cycles

PubMed Central

Apriasz, Rafał; Krueger, Tyll; Marcjasz, Grzegorz; Sznajd-Weron, Katarzyna

2016-01-01

We study a simple agent-based model of the recurring fashion cycles in the society that consists of two interacting communities: “snobs” and “followers” (or “opinion hunters”, hence the name of the model). Followers conform to all other individuals, whereas snobs conform only to their own group and anticonform to the other. The model allows to examine the role of the social structure, i.e. the influence of the number of inter-links between the two communities, as well as the role of the stability of links. The latter is accomplished by considering two versions of the same model—quenched (parameterized by fraction L of fixed inter-links) and annealed (parameterized by probability p that a given inter-link exists). Using Monte Carlo simulations and analytical treatment (the latter only for the annealed model), we show that there is a critical fraction of inter-links, above which recurring cycles occur. For p ≤ 0.5 we derive a relation between parameters L and p that allows to compare both models and show that the critical value of inter-connections, p*, is the same for both versions of the model (annealed and quenched) but the period of a fashion cycle is shorter for the quenched model. Near the critical point, the cycles are irregular and a change of fashion is difficult to predict. For the annealed model we also provide a deeper theoretical analysis. We conjecture on topological grounds that the so-called saddle node heteroclinic bifurcation appears at p*. For p ≥ 0.5 we show analytically the existence of the second critical value of p, for which the system undergoes Hopf’s bifurcation. PMID:27835679

Distributed event-triggered consensus strategy for multi-agent systems under limited resources

NASA Astrophysics Data System (ADS)

Noorbakhsh, S. Mohammad; Ghaisari, Jafar

2016-01-01

The paper proposes a distributed structure to address an event-triggered consensus problem for multi-agent systems which aims at concurrent reduction in inter-agent communication, control input actuation and energy consumption. Following the proposed approach, asymptotic convergence of all agents to consensus requires that each agent broadcasts its sampled-state to the neighbours and updates its control input only at its own triggering instants, unlike the existing related works. Obviously, it decreases the network bandwidth usage, sensor energy consumption, computation resources usage and actuator wears. As a result, it facilitates the implementation of the proposed consensus protocol in the real-world applications with limited resources. The stability of the closed-loop system under an event-based protocol is proved analytically. Some numerical results are presented which confirm the analytical discussion on the effectiveness of the proposed design.

Phase transitions in adaptive competitive environments: Theories and applications of the minority game

NASA Astrophysics Data System (ADS)

Li, Yi

It is of great scientific significance to study the complex systems of agents with adaptive strategies competing for resources. In many of such systems in social and biological environments, agents succeed by making innovative choices. In this thesis, we model this behavior by presenting the results and analysis of a class of games in which heterogeneous agents are rewarded for being in a minority group. Each agent possesses a number of fixed strategies, each of which takes publicly available information as input to predict next group. Commonly known as the minority game, this simple model manifests a maladaptive, informationally efficient phase in which the system performs poorly at generating resources and an inefficient phase in which there is an emergent cooperation among the agents, and the system more effectively generates resources. The best emergent coordination is achieved at the phase transition, which occurs when z, the ratio of the dimension of the strategy space to the number of agents, is about 0.34. This model also has similar properties to a spin glass system thus statistical mechanics methods were employed to provide analytical results. The phase structure persists under variations such as variable payoff schemes and evolutionary mechanisms. Agents in real life are subject to local connectivity and incomplete information. A framework based on bi-graph was proposed to model these factors. In the context of economics, we proposed a stock market model incorporating delayed majority dynamics and agents holding heterogeneous expectations. We found that for a range of parameter settings, minority dynamics are dynamically induced, effectively reducing market volatility. Finally, we introduce a version of the minority game played by human participants. We observed emergent coordination of players' choices leading to increased average reward. Furthermore, players with the simplest strategies reap the most wealth.

An Autonomous Mobile Agent-Based Distributed Learning Architecture: A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

Current distance learning systems are increasingly packing highly data-intensive contents on servers, resulting in the congestion of network and server resources at peak service times. A distributed learning system based on faded information field (FIF) architecture that employs mobile agents (MAs) has been proposed and simulated in this work. The…

Nitrogen Trifluoride-Based Fluoride- Volatility Separations Process: Initial Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

McNamara, Bruce K.; Scheele, Randall D.; Casella, Andrew M.

2011-09-28

This document describes the results of our investigations on the potential use of nitrogen trifluoride as the fluorinating and oxidizing agent in fluoride volatility-based used nuclear fuel reprocessing. The conceptual process uses differences in reaction temperatures between nitrogen trifluoride and fuel constituents that produce volatile fluorides to achieve separations and recover valuable constituents. We provide results from our thermodynamic evaluations, thermo-analytical experiments, kinetic models, and provide a preliminary process flowsheet. The evaluations found that nitrogen trifluoride can effectively produce volatile fluorides at different temperatures dependent on the fuel constituent.

Environmental Sustainability and Effects on Urban Micro Region using Agent-Based Modeling of Urbanisation in Select Major Indian Cities

NASA Astrophysics Data System (ADS)

Aithal, B. H.

2015-12-01

Abstract: Urbanisation has gained momentum with globalization in India. Policy decisions to set up commercial, industrial hubs have fuelled large scale migration, added with population upsurge has contributed to the fast growing urban region that needs to be monitored in order to design sustainable urban cities. Unplanned urbanization have resulted in the growth of peri-urban region referred to as urban sprawl, are often devoid of basic amenities and infrastructure leading to large scale environmental problems that are evident. Remote sensing data acquired through space borne sensors at regular interval helps in understanding urban dynamics aided by Geoinformatics which has proved very effective in mapping and monitoring for sustainable urban planning. Cellular automata (CA) is a robust approach for the spatially explicit simulation of land-use land cover dynamics. CA uses rules, states, conditions that are vital factors in modelling urbanisation. This communication effectively introduces simulation assistances of CA with the agent based modelling supported by its fuzzy characteristics and weightages through analytical hierarchal process (AHP). This has been done considering perceived agents such as industries, natural resource etc. Respective agent's role in development of a particular regions into an urban area has been examined with weights and its influence of each of these agents based on its characteristics functions. Validation was performed obtaining a high kappa coefficient indicating the quality and the allocation performance of the model & validity of the model to predict future projections. The prediction using the proposed model was performed for 2030. Further environmental sustainability of each of these cities are explored such as water features, environment, greenhouse gas emissions, effects on human human health etc., Modeling suggests trend of various land use classes transformation with the spurt in urban expansions based on specific regions and policies providing a visual spatial information to both urban planners and city managers. Further environmental sustainability assessment indicates dwindling natural resources and increase in thermal discomfort to the living population thereby indicating need for balanced and planned development.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yongzheng, E-mail: yzsung@gmail.com; Li, Wang; Zhao, Donghua

In this paper, we propose a new consensus model in which the interactions among agents stochastically switch between attraction and repulsion. Such a positive-and-negative mechanism is described by the white-noise-based coupling. Analytic criteria for the consensus and non-consensus in terms of the eigenvalues of the noise intensity matrix are derived, which provide a better understanding of the constructive roles of random interactions. Specifically, we discover a positive role of noise coupling that noise can accelerate the emergence of consensus. We find that the converging speed of the multi-agent network depends on the square of the second smallest eigenvalue of itsmore » graph Laplacian. The influence of network topologies on the consensus time is also investigated.« less

A molecularly imprinted polymer (MIP)-coated microbeam MEMS sensor for chemical detection

NASA Astrophysics Data System (ADS)

Holthoff, Ellen L.; Li, Lily; Hiller, Tobias; Turner, Kimberly L.

2015-05-01

Recently, microcantilever-based technology has emerged as a viable sensing platform due to its many advantages such as small size, high sensitivity, and low cost. However, microcantilevers lack the inherent ability to selectively identify hazardous chemicals (e.g., explosives, chemical warfare agents). The key to overcoming this challenge is to functionalize the top surface of the microcantilever with a receptor material (e.g., a polymer coating) so that selective binding between the cantilever and analyte of interest takes place. Molecularly imprinted polymers (MIPs) can be utilized as artificial recognition elements for target chemical analytes of interest. Molecular imprinting involves arranging polymerizable functional monomers around a template molecule followed by polymerization and template removal. The selectivity for the target analyte is based on the spatial orientation of the binding site and covalent or noncovalent interactions between the functional monomer and the analyte. In this work, thin films of sol-gel-derived xerogels molecularly imprinted for TNT and dimethyl methylphosphonate (DMMP), a chemical warfare agent stimulant, have demonstrated selectivity and stability in combination with a fixed-fixed beam microelectromechanical systems (MEMS)-based gas sensor. The sensor was characterized by parametric bifurcation noise-based tracking.

Portable Analytical Systems for On-Site Diagnosis of Exposure to Pesticides and Nerve Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yuehe; Wang, Jun; Liu, Guodong

In this chapter, we summarize recent work in our laboratory on the development of sensitive portable analytical systems for use in on-site detection of exposure to organophosphate (OP) pesticides and chemical nerve agents. These systems are based on various nanomaterials functioning as transducers; recognition agents or labels and various elelectrochemical/immunoassay techniques. The studied nanomaterials included functionalized carbon nanotubes (CNT), zirconia nanoparticles (NPs) and quantum dots (QDs). Three biomarkers e.g. the free OPs, metabolites of OPs and protein-OP adducts in biological matrices have been employed for biomonitoring of OP exposure with our developed system. It has been found that the nanomaterial-basedmore » portable analytical systems have high sensitivity for the detection of the biomarkers, which suggest that these technologies offer great promise for the rapid and on-site detection and evaluation of OP exposure.« less

Dynamical systems approach to the study of a sociophysics agent-based model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timpanaro, Andre M.; Prado, Carmen P. C.

2011-03-24

The Sznajd model is a Potts-like model that has been studied in the context of sociophysics [1,2](where spins are interpreted as opinions). In a recent work [3], we generalized the Sznajd model to include assymetric interactions between the spins (interpreted as biases towards opinions) and used dynamical systems techniques to tackle its mean-field version, given by the flow: {eta}{sub {sigma}} = {Sigma}{sub {sigma}}'{sup M} = 1{eta}{sub {sigma}}{eta}{sigma}'({eta}{sub {sigma}}{rho}{sigma}'{yields}{sigma}-{sigma}'{rho}{sigma}{yields}{sigma}').Where hs is the proportion of agents with opinion (spin){sigma}', M is the number of opinions and {sigma}'{yields}{sigma}' is the probability weight for an agent with opinion {sigma} being convinced by another agentmore » with opinion {sigma}'. We made Monte Carlo simulations of the model in a complex network (using Barabasi-Albert networks [4]) and they displayed the same attractors than the mean-field. Using linear stability analysis, we were able to determine the mean-field attractor structure analytically and to show that it has connections with well known graph theory problems (maximal independent sets and positive fluxes in directed graphs). Our dynamical systems approach is quite simple and can be used also in other models, like the voter model.« less

A capillary electrophoresis chip for the analysis of print and film photographic developing agents in commercial processing solutions using indirect fluorescence detection.

PubMed

Sirichai, S; de Mello, A J

2001-01-01

The separation and detection of both print and film developing agents (CD-3 and CD-4) in photographic processing solutions using chip-based capillary electrophoresis is presented. For simultaneous detection of both analytes under identical experimental conditions a buffer pH of 11.9 is used to partially ionise the analytes. Detection is made possible by indirect fluorescence, where the ions of the analytes displace the anionic fluorescing buffer ion to create negative peaks. Under optimal conditions, both analytes can be analyzed within 30 s. The limits of detection for CD-3 and CD-4 are 0.17 mM and 0.39 mM, respectively. The applicability of the method for the analysis of seasoned photographic processing developer solutions is also examined.

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

Cost-effectiveness of a novel blood-pool contrast agent in the setting of chest pain evaluation in an emergency department.

PubMed

Espinosa, Gabriela; Annapragada, Ananth

2013-10-01

We evaluated three diagnostic strategies with the objective of comparing the current standard of care for individuals presenting acute chest pain and no history of coronary artery disease (CAD) with a novel diagnostic strategy using an emerging technology (blood-pool contrast agent [BPCA]) to identify the potential benefits and cost reductions. A decision analytic model of diagnostic strategies and outcomes using a BPCA and a conventional agent for CT angiography (CTA) in patients with acute chest pain was built. The model was used to evaluate three diagnostic strategies: CTA using a BPCA followed by invasive coronary angiography (ICA), CTA using a conventional agent followed by ICA, and ICA alone. The use of the two CTA-based triage tests before ICA in a population with a CAD prevalence of less than 47% was predicted to be more cost-effective than ICA alone. Using the base-case values and a cost premium for BPCA over the conventional CT agent (cost of BPCA ≈ 5× that of a conventional agent) showed that CTA with a BPCA before ICA resulted in the most cost-effective strategy; the other strategies were ruled out by simple dominance. The model strongly depends on the rates of complications from the diagnostic tests included in the model. In a population with an elevated risk of contrast-induced nephropathy (CIN), a significant premium cost per BPCA dose still resulted in the alternative whereby CTA using BPCA was more cost-effective than CTA using a conventional agent. A similar effect was observed for potential complications resulting from the BPCA injection. Conversely, in the presence of a similar complication rate from BPCA, the diagnostic strategy of CTA using a conventional agent would be the optimal alternative. BPCAs could have a significant impact in the diagnosis of acute chest pain, in particular for populations with high incidences of CIN. In addition, a BPCA strategy could garner further savings if currently excluded phenomena including renal disease and incidental findings were included in the decision model.

Chemical and biological threat-agent detection using electrophoresis-based lab-on-a-chip devices.

PubMed

Borowsky, Joseph; Collins, Greg E

2007-10-01

The ability to separate complex mixtures of analytes has made capillary electrophoresis (CE) a powerful analytical tool since its modern configuration was first introduced over 25 years ago. The technique found new utility with its application to the microfluidics based lab-on-a-chip platform (i.e., microchip), which resulted in ever smaller footprints, sample volumes, and analysis times. These features, coupled with the technique's potential for portability, have prompted recent interest in the development of novel analyzers for chemical and biological threat agents. This article will comment on three main areas of microchip CE as applied to the separation and detection of threat agents: detection techniques and their corresponding limits of detection, sampling protocol and preparation time, and system portability. These three areas typify the broad utility of lab-on-a-chip for meeting critical, present-day security, in addition to illustrating areas wherein advances are necessary.

μ-PADs for detection of chemical warfare agents.

PubMed

Pardasani, Deepak; Tak, Vijay; Purohit, Ajay K; Dubey, D K

2012-12-07

Conventional methods of detection of chemical warfare agents (CWAs) based on chromogenic reactions are time and solvent intensive. The development of cost, time and solvent effective microfluidic paper based analytical devices (μ-PADs) for the detection of nerve and vesicant agents is described. The detection of analytes was based upon their reactions with rhodamine hydroxamate and para-nitrobenzyl pyridine, producing red and blue colours respectively. Reactions were optimized on the μ-PADs to produce the limits of detection (LODs) as low as 100 μM for sulfur mustard in aqueous samples. Results were quantified with the help of a simple desktop scanner and Photoshop software. Sarin achieved a linear response in the two concentration ranges of 20-100 mM and 100-500 mM, whereas the response of sulfur mustard was found to be linear in the concentration range of 10-75 mM. Results were precise enough to establish the μ-PADs as a valuable tool for security personnel fighting against chemical terrorism.

Multiagent model and mean field theory of complex auction dynamics

NASA Astrophysics Data System (ADS)

Chen, Qinghua; Huang, Zi-Gang; Wang, Yougui; Lai, Ying-Cheng

2015-09-01

Recent years have witnessed a growing interest in analyzing a variety of socio-economic phenomena using methods from statistical and nonlinear physics. We study a class of complex systems arising from economics, the lowest unique bid auction (LUBA) systems, which is a recently emerged class of online auction game systems. Through analyzing large, empirical data sets of LUBA, we identify a general feature of the bid price distribution: an inverted J-shaped function with exponential decay in the large bid price region. To account for the distribution, we propose a multi-agent model in which each agent bids stochastically in the field of winner’s attractiveness, and develop a theoretical framework to obtain analytic solutions of the model based on mean field analysis. The theory produces bid-price distributions that are in excellent agreement with those from the real data. Our model and theory capture the essential features of human behaviors in the competitive environment as exemplified by LUBA, and may provide significant quantitative insights into complex socio-economic phenomena.

Intelligent systems in the context of surrounding environment.

PubMed

Wakeling, J; Bak, P

2001-11-01

We investigate the behavioral patterns of a population of agents, each controlled by a simple biologically motivated neural network model, when they are set in competition against each other in the minority model of Challet and Zhang. We explore the effects of changing agent characteristics, demonstrating that crowding behavior takes place among agents of similar memory, and show how this allows unique "rogue" agents with higher memory values to take advantage of a majority population. We also show that agents' analytic capability is largely determined by the size of the intermediary layer of neurons. In the context of these results, we discuss the general nature of natural and artificial intelligence systems, and suggest intelligence only exists in the context of the surrounding environment (embodiment).

Modeling the dynamics of dissent

NASA Astrophysics Data System (ADS)

Lee, Eun; Holme, Petter; Lee, Sang Hoon

2017-11-01

We investigate the formation of opinion against authority in an authoritarian society composed of agents with different levels of authority. We explore a ;dissenting; opinion, held by lower-ranking, obedient, or less authoritative people, spreading in an environment of an ;affirmative; opinion held by authoritative leaders. A real-world example would be a corrupt society where people revolt against such leaders, but it can be applied to more general situations. In our model, agents can change their opinion depending on their authority relative to their neighbors and their own confidence level. In addition, with a certain probability, agents can override the affirmative opinion to take the dissenting opinion of a neighbor. Based on analytic derivation and numerical simulations, we observe that both the network structure and heterogeneity in authority, and their correlation, significantly affect the possibility of the dissenting opinion to spread through the population. In particular, the dissenting opinion is suppressed when the authority distribution is very heterogeneous and there exists a positive correlation between the authority and the number of neighbors of people (degree). Except for such an extreme case, though, spreading of the dissenting opinion takes place when people have the tendency to override the authority to hold the dissenting opinion, but the dissenting opinion can take a long time to spread to the entire society, depending on the model parameters. We argue that the internal social structure of agents sets the scale of the time to reach consensus, based on the analysis of the underlying structural properties of opinion spreading.

Reevaluation of 1999 Health-Based Environmental Screening Levels (HBESLs) for Chemical Warfare Agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watson, Annetta Paule; Dolislager, Fredrick G

2007-05-01

This report evaluates whether new information and updated scientific models require that changes be made to previously published health-based environmental soil screening levels (HBESLs) and associated environmental fate/breakdown information for chemical warfare agents (USACHPPM 1999). Specifically, the present evaluation describes and compares changes that have been made since 1999 to U.S. Environmental Protection Agency (EPA) risk assessment models, EPA exposure assumptions, as well as to specific chemical warfare agent parameters (e.g., toxicity values). Comparison was made between screening value estimates recalculated with current assumptions and earlier health-based environmental screening levels presented in 1999. The chemical warfare agents evaluated include themore » G-series and VX nerve agents and the vesicants sulfur mustard (agent HD) and Lewisite (agent L). In addition, key degradation products of these agents were also evaluated. Study findings indicate that the combined effect of updates and/or changes to EPA risk models, EPA default exposure parameters, and certain chemical warfare agent toxicity criteria does not result in significant alteration to the USACHPPM (1999) health-based environmental screening level estimates for the G-series and VX nerve agents or the vesicant agents HD and L. Given that EPA's final position on separate Tier 1 screening levels for indoor and outdoor worker screening assessments has not yet been released as of May 2007, the study authors find that the 1999 screening level estimates (see Table ES.1) are still appropriate and protective for screening residential as well as nonresidential sites. As such, risk management decisions made on the basis of USACHPPM (1999) recommendations do not require reconsideration. While the 1999 HBESL values are appropriate for continued use as general screening criteria, the updated '2007' estimates (presented below) that follow the new EPA protocols currently under development are also protective. When EPA finalizes and documents a position on the matter of indoor and outdoor worker screening assessments, site-specific risk assessments should make use of modified models and criteria. Screening values such as those presented in this report may be used to assess soil or other porous media to determine whether chemical warfare agent contamination is present as part of initial site investigations (whether due to intentional or accidental releases) and to determine whether weather/decontamination has adequately mitigated the presence of agent residual to below levels of concern. However, despite the availability of scientifically supported health-based criteria, there are significant resources needs that should be considered during sample planning. In particular, few analytical laboratories are likely to be able to meet these screening levels. Analyses will take time and usually have limited confidence at these concentrations. Therefore, and particularly for the more volatile agents, soil/destructive samples of porous media should be limited and instead enhanced with headspace monitoring and presence-absence wipe sampling.« less

Special issue on Military Operations Research Society (MORS) Symposium (80th): Expanding the Boundaries of National Security Analysis (Phalanx: The Bulletin of Military Operations Research. Volume 45, Number 2, June 2012)

DTIC Science & Technology

2012-06-01

brianmccue@alum.mit.edu Letters to the Editor, John Willis, Augustine Consulting, Inc., jwillis@aciedge.com Modeling and Simulation , James N. Bexfield, FS, OSD...concepts that are now being applied to modern analytical thinking. The tuto- rials are free to MORS members and $75 for the day for nonmembers. The...Overview of Agent- based Modeling and Simulation and Complex Adaptive Systems •  Visual Data Analysis •  Analyzing Combat Identification •  Guidelines for

Evolution of cooperative strategies from first principles.

PubMed

Burtsev, Mikhail; Turchin, Peter

2006-04-20

One of the greatest challenges in the modern biological and social sciences is to understand the evolution of cooperative behaviour. General outlines of the answer to this puzzle are currently emerging as a result of developments in the theories of kin selection, reciprocity, multilevel selection and cultural group selection. The main conceptual tool used in probing the logical coherence of proposed explanations has been game theory, including both analytical models and agent-based simulations. The game-theoretic approach yields clear-cut results but assumes, as a rule, a simple structure of payoffs and a small set of possible strategies. Here we propose a more stringent test of the theory by developing a computer model with a considerably extended spectrum of possible strategies. In our model, agents are endowed with a limited set of receptors, a set of elementary actions and a neural net in between. Behavioural strategies are not predetermined; instead, the process of evolution constructs and reconstructs them from elementary actions. Two new strategies of cooperative attack and defence emerge in simulations, as well as the well-known dove, hawk and bourgeois strategies. Our results indicate that cooperative strategies can evolve even under such minimalist assumptions, provided that agents are capable of perceiving heritable external markers of other agents.

Trophallaxis-inspired model for distributed transport between randomly interacting agents

NASA Astrophysics Data System (ADS)

Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.; Katifori, Eleni

2017-08-01

Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

Trophallaxis-inspired model for distributed transport between randomly interacting agents.

PubMed

Gräwer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G; Katifori, Eleni

2017-08-01

Trophallaxis, the regurgitation and mouth to mouth transfer of liquid food between members of eusocial insect societies, is an important process that allows the fast and efficient dissemination of food in the colony. Trophallactic systems are typically treated as a network of agent interactions. This approach, though valuable, does not easily lend itself to analytic predictions. In this work we consider a simple trophallactic system of randomly interacting agents with finite carrying capacity, and calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess to what level the observed food uptake rates and efficiency in food distribution is due to stochastic effects or specific trophallactic strategies by the ant colony. Our work also serves as a stepping stone to describing the collective properties of more complex trophallactic systems, such as those including division of labor between foragers and workers.

Enzyme Biosensors for Biomedical Applications: Strategies for Safeguarding Analytical Performances in Biological Fluids

PubMed Central

Rocchitta, Gaia; Spanu, Angela; Babudieri, Sergio; Latte, Gavinella; Madeddu, Giordano; Galleri, Grazia; Nuvoli, Susanna; Bagella, Paola; Demartis, Maria Ilaria; Fiore, Vito; Manetti, Roberto; Serra, Pier Andrea

2016-01-01

Enzyme-based chemical biosensors are based on biological recognition. In order to operate, the enzymes must be available to catalyze a specific biochemical reaction and be stable under the normal operating conditions of the biosensor. Design of biosensors is based on knowledge about the target analyte, as well as the complexity of the matrix in which the analyte has to be quantified. This article reviews the problems resulting from the interaction of enzyme-based amperometric biosensors with complex biological matrices containing the target analyte(s). One of the most challenging disadvantages of amperometric enzyme-based biosensor detection is signal reduction from fouling agents and interference from chemicals present in the sample matrix. This article, therefore, investigates the principles of functioning of enzymatic biosensors, their analytical performance over time and the strategies used to optimize their performance. Moreover, the composition of biological fluids as a function of their interaction with biosensing will be presented. PMID:27249001

Chemical analysis of bleach and hydroxide-based solutions after decontamination of the chemical warfare agent O-ethyl S-2-diisopropylaminoethyl methylphosphonothiolate (VX).

PubMed

Hopkins, F B; Gravett, M R; Self, A J; Wang, M; Chua, Hoe-Chee; Hoe-Chee, C; Lee, H S Nancy; Sim, N Lee Hoi; Jones, J T A; Timperley, C M; Riches, J R

2014-08-01

Detailed chemical analysis of solutions used to decontaminate chemical warfare agents can be used to support verification and forensic attribution. Decontamination solutions are amongst the most difficult matrices for chemical analysis because of their corrosive and potentially emulsion-based nature. Consequently, there are relatively few publications that report their detailed chemical analysis. This paper describes the application of modern analytical techniques to the analysis of decontamination solutions following decontamination of the chemical warfare agent O-ethyl S-2-diisopropylaminoethyl methylphosphonothiolate (VX). We confirm the formation of N,N-diisopropylformamide and N,N-diisopropylamine following decontamination of VX with hypochlorite-based solution, whereas they were not detected in extracts of hydroxide-based decontamination solutions by nuclear magnetic resonance (NMR) spectroscopy or gas chromatography-mass spectrometry. We report the electron ionisation and chemical ionisation mass spectroscopic details, retention indices, and NMR spectra of N,N-diisopropylformamide and N,N-diisopropylamine, as well as analytical methods suitable for their analysis and identification in solvent extracts and decontamination residues.

Using uncertainty and sensitivity analyses in socioecological agent-based models to improve their analytical performance and policy relevance.

PubMed

Ligmann-Zielinska, Arika; Kramer, Daniel B; Spence Cheruvelil, Kendra; Soranno, Patricia A

2014-01-01

Agent-based models (ABMs) have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1) efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2) conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system.

Using Uncertainty and Sensitivity Analyses in Socioecological Agent-Based Models to Improve Their Analytical Performance and Policy Relevance

PubMed Central

Ligmann-Zielinska, Arika; Kramer, Daniel B.; Spence Cheruvelil, Kendra; Soranno, Patricia A.

2014-01-01

Agent-based models (ABMs) have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1) efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2) conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system. PMID:25340764

Using analytic hierarchy process approach in ontological multicriterial decision making - Preliminary considerations

NASA Astrophysics Data System (ADS)

Wasielewska, K.; Ganzha, M.

2012-10-01

In this paper we consider combining ontologically demarcated information with Saaty's Analytic Hierarchy Process (AHP) [1] for the multicriterial assessment of offers during contract negotiations. The context for the proposal is provided by the Agents in Grid project (AiG; [2]), which aims at development of an agent-based infrastructure for efficient resource management in the Grid. In the AiG project, software agents representing users can either (1) join a team and earn money, or (2) find a team to execute a job. Moreover, agents form teams, managers of which negotiate with clients and workers terms of potential collaboration. Here, ontologically described contracts (Service Level Agreements) are the results of autonomous multiround negotiations. Therefore, taking into account relatively complex nature of the negotiated contracts, multicriterial assessment of proposals plays a crucial role. The AHP method is based on pairwise comparisons of criteria and relies on the judgement of a panel of experts. It measures how well does an offer serve the objective of a decision maker. In this paper, we propose how the AHP method can be used to assess ontologically described contract proposals.

Functionalized gold nanoparticle supported sensory mechanisms applied in detection of chemical and biological threat agents: a review.

PubMed

Upadhyayula, Venkata K K

2012-02-17

There is a great necessity for development of novel sensory concepts supportive of smart sensing capabilities in defense and homeland security applications for detection of chemical and biological threat agents. A smart sensor is a detection device that can exhibit important features such as speed, sensitivity, selectivity, portability, and more importantly, simplicity in identifying a target analyte. Emerging nanomaterial based sensors, particularly those developed by utilizing functionalized gold nanoparticles (GNPs) as a sensing component potentially offer many desirable features needed for threat agent detection. The sensitiveness of physical properties expressed by GNPs, e.g. color, surface plasmon resonance, electrical conductivity and binding affinity are significantly enhanced when they are subjected to functionalization with an appropriate metal, organic or biomolecular functional groups. This sensitive nature of functionalized GNPs can be potentially exploited in the design of threat agent detection devices with smart sensing capabilities. In the presence of a target analyte (i.e., a chemical or biological threat agent) a change proportional to concentration of the analyte is observed, which can be measured either by colorimetric, fluorimetric, electrochemical or spectroscopic means. This article provides a review of how functionally modified gold colloids are applied in the detection of a broad range of threat agents, including radioactive substances, explosive compounds, chemical warfare agents, biotoxins, and biothreat pathogens through any of the four sensory means mentioned previously. Copyright © 2011 Elsevier B.V. All rights reserved.

History and perspectives of bioanalytical methods for chemical warfare agent detection.

PubMed

Black, Robin M

2010-05-15

This paper provides a short historical overview of the development of bioanalytical methods for chemical warfare (CW) agents and their biological markers of exposure, with a more detailed overview of methods for organophosphorus nerve agents. Bioanalytical methods for unchanged CW agents are used primarily for toxicokinetic/toxicodynamic studies. An important aspect of nerve agent toxicokinetics is the different biological activity and detoxification pathways for enantiomers. CW agents have a relatively short lifetime in the human body, and are hydrolysed, metabolised, or adducted to nucleophilic sites on macromolecules such as proteins and DNA. These provide biological markers of exposure. In the past two decades, metabolites, protein adducts of nerve agents, vesicants and phosgene, and DNA adducts of sulfur and nitrogen mustards, have been identified and characterized. Sensitive analytical methods have been developed for their detection, based mainly on mass spectrometry combined with gas or liquid chromatography. Biological markers for sarin, VX and sulfur mustard have been validated in cases of accidental and deliberate human exposures. The concern for terrorist use of CW agents has stimulated the development of higher throughput analytical methods in support of homeland security. Copyright (c) 2010. Published by Elsevier B.V.

Fate of the chemical warfare agent O-ethyl S-2-diisopropylaminoethyl methylphosphonothiolate (VX) on soil following accelerant-based fire and liquid decontamination.

PubMed

Gravett, M R; Hopkins, F B; Self, A J; Webb, A J; Timperley, C M; Riches, J R

2014-08-01

In the event of alleged use of organophosphorus nerve agents, all kinds of environmental samples can be received for analysis. These might include decontaminated and charred matter collected from the site of a suspected chemical attack. In other scenarios, such matter might be sampled to confirm the site of a chemical weapon test or clandestine laboratory decontaminated and burned to prevent discovery. To provide an analytical capability for these contingencies, we present a preliminary investigation of the effect of accelerant-based fire and liquid decontamination on soil contaminated with the nerve agent O-ethyl S-2-diisopropylaminoethyl methylphosphonothiolate (VX). The objectives were (a) to determine if VX or its degradation products were detectable in soil after an accelerant-based fire promoted by aviation fuel, including following decontamination with Decontamination Solution 2 (DS2) or aqueous sodium hypochlorite, (b) to develop analytical methods to support forensic analysis of accelerant-soaked, decontaminated and charred soil and (c) to inform the design of future experiments of this type to improve analytical fidelity. Our results show for the first time that modern analytical techniques can be used to identify residual VX and its degradation products in contaminated soil after an accelerant-based fire and after chemical decontamination and then fire. Comparison of the gas chromatography-mass spectrometry (GC-MS) profiles of VX and its impurities/degradation products from contaminated burnt soil, and burnt soil spiked with VX, indicated that the fire resulted in the production of diethyl methylphosphonate and O,S-diethyl methylphosphonothiolate (by an unknown mechanism). Other products identified were indicative of chemical decontamination, and some of these provided evidence of the decontaminant used, for example, ethyl 2-methoxyethyl methylphosphonate and bis(2-methoxyethyl) methylphosphonate following decontamination with DS2. Sample preparation procedures and analytical methods suitable for investigating accelerant and decontaminant-soaked soil samples are presented. VX and its degradation products and/or impurities were detected under all the conditions studied, demonstrating that accelerant-based fire and liquid-based decontamination and then fire are unlikely to prevent the retrieval of evidence of chemical warfare agent (CWA) testing. This is the first published study of the effects of an accelerant-based fire on a CWA in environmental samples. The results will inform defence and security-based organisations worldwide and support the verification activities of the Organisation for the Prohibition of Chemical Weapons (OPCW), winner of the 2013 Nobel Peace Prize for its extensive efforts to eliminate chemical weapons.

Experimental econophysics: Complexity, self-organization, and emergent properties

NASA Astrophysics Data System (ADS)

Huang, J. P.

2015-03-01

Experimental econophysics is concerned with statistical physics of humans in the laboratory, and it is based on controlled human experiments developed by physicists to study some problems related to economics or finance. It relies on controlled human experiments in the laboratory together with agent-based modeling (for computer simulations and/or analytical theory), with an attempt to reveal the general cause-effect relationship between specific conditions and emergent properties of real economic/financial markets (a kind of complex adaptive systems). Here I review the latest progress in the field, namely, stylized facts, herd behavior, contrarian behavior, spontaneous cooperation, partial information, and risk management. Also, I highlight the connections between such progress and other topics of traditional statistical physics. The main theme of the review is to show diverse emergent properties of the laboratory markets, originating from self-organization due to the nonlinear interactions among heterogeneous humans or agents (complexity).

A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

NASA Technical Reports Server (NTRS)

Lee, S. Daniel

1990-01-01

We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.

Optimal harvesting for a predator-prey agent-based model using difference equations.

PubMed

Oremland, Matthew; Laubenbacher, Reinhard

2015-03-01

In this paper, a method known as Pareto optimization is applied in the solution of a multi-objective optimization problem. The system in question is an agent-based model (ABM) wherein global dynamics emerge from local interactions. A system of discrete mathematical equations is formulated in order to capture the dynamics of the ABM; while the original model is built up analytically from the rules of the model, the paper shows how minor changes to the ABM rule set can have a substantial effect on model dynamics. To address this issue, we introduce parameters into the equation model that track such changes. The equation model is amenable to mathematical theory—we show how stability analysis can be performed and validated using ABM data. We then reduce the equation model to a simpler version and implement changes to allow controls from the ABM to be tested using the equations. Cohen's weighted κ is proposed as a measure of similarity between the equation model and the ABM, particularly with respect to the optimization problem. The reduced equation model is used to solve a multi-objective optimization problem via a technique known as Pareto optimization, a heuristic evolutionary algorithm. Results show that the equation model is a good fit for ABM data; Pareto optimization provides a suite of solutions to the multi-objective optimization problem that can be implemented directly in the ABM.

Human performance modeling for system of systems analytics: combat performance-shaping factors.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawton, Craig R.; Miller, Dwight Peter

The US military has identified Human Performance Modeling (HPM) as a significant requirement and challenge of future systems modeling and analysis initiatives. To support this goal, Sandia National Laboratories (SNL) has undertaken a program of HPM as an integral augmentation to its system-of-system (SoS) analytics capabilities. The previous effort, reported in SAND2005-6569, evaluated the effects of soldier cognitive fatigue on SoS performance. The current effort began with a very broad survey of any performance-shaping factors (PSFs) that also might affect soldiers performance in combat situations. The work included consideration of three different approaches to cognition modeling and how appropriate theymore » would be for application to SoS analytics. This bulk of this report categorizes 47 PSFs into three groups (internal, external, and task-related) and provides brief descriptions of how each affects combat performance, according to the literature. The PSFs were then assembled into a matrix with 22 representative military tasks and assigned one of four levels of estimated negative impact on task performance, based on the literature. Blank versions of the matrix were then sent to two ex-military subject-matter experts to be filled out based on their personal experiences. Data analysis was performed to identify the consensus most influential PSFs. Results indicate that combat-related injury, cognitive fatigue, inadequate training, physical fatigue, thirst, stress, poor perceptual processing, and presence of chemical agents are among the PSFs with the most negative impact on combat performance.« less

Literature and Product Review of Visual Analytics for Maritime Awareness

DTIC Science & Technology

2009-10-28

the user’s knowledge and experience. • Riveiro et al [107] provide a useful discussion of the cognitive process of anomaly detection based on...changes over time can be seen visually. • Wilkinson et al [140] suggests that we need visual analytics for three principal purposes: checking raw data...Predictions within the Current Plot • Yue et al [146] describe an AI blackboard-based agent that leverages interactive visualization and mixed

The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

PubMed Central

Aguilera, Miguel; Bedia, Manuel G.; Santos, Bruno A.; Barandiaran, Xabier E.

2013-01-01

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose “brain” is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of mind. PMID:23986692

Self-organization in a simple model of adaptive agents playing 2×2 games with arbitrary payoff matrices

NASA Astrophysics Data System (ADS)

Fort, H.; Viola, S.

2004-03-01

We analyze, both analytically and numerically, the self-organization of a system of “selfish” adaptive agents playing an arbitrary iterated pairwise game (defined by a 2×2 payoff matrix). Examples of possible games to play are the prisoner’s dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor “tags” and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation ceq. Depending on the payoff matrix, we show that ceq can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of ceq can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of “antisocial” individuals—incapable of realizing any value to cooperation—on the cooperative regime hold by a population of neutral or “normal” agents.

Self-organization in a simple model of adaptive agents playing 2 x 2 games with arbitrary payoff matrices.

PubMed

Fort, H; Viola, S

2004-03-01

We analyze, both analytically and numerically, the self-organization of a system of "selfish" adaptive agents playing an arbitrary iterated pairwise game (defined by a 2 x 2 payoff matrix). Examples of possible games to play are the prisoner's dilemma (PD) game, the chicken game, the hero game, etc. The agents have no memory, use strategies not based on direct reciprocity nor "tags" and are chosen at random, i.e., geographical vicinity is neglected. They can play two possible strategies: cooperate (C) or defect (D). The players measure their success by comparing their utilities with an estimate for the expected benefits and update their strategy following a simple rule. Two versions of the model are studied: (1) the deterministic version (the agents are either in definite states C or D) and (2) the stochastic version (the agents have a probability c of playing C). Using a general master equation we compute the equilibrium states into which the system self-organizes, characterized by their average probability of cooperation c(eq). Depending on the payoff matrix, we show that c(eq) can take five different values. We also consider the mixing of agents using two different payoff matrices and show that any value of c(eq) can be reached by tuning the proportions of agents using each payoff matrix. In particular, this can be used as a way to simulate the effect of a fraction d of "antisocial" individuals--incapable of realizing any value to cooperation--on the cooperative regime hold by a population of neutral or "normal" agents.

A fractional reaction-diffusion description of supply and demand

NASA Astrophysics Data System (ADS)

Benzaquen, Michael; Bouchaud, Jean-Philippe

2018-02-01

We suggest that the broad distribution of time scales in financial markets could be a crucial ingredient to reproduce realistic price dynamics in stylised Agent-Based Models. We propose a fractional reaction-diffusion model for the dynamics of latent liquidity in financial markets, where agents are very heterogeneous in terms of their characteristic frequencies. Several features of our model are amenable to an exact analytical treatment. We find in particular that the impact is a concave function of the transacted volume (aka the "square-root impact law"), as in the normal diffusion limit. However, the impact kernel decays as t-β with β = 1/2 in the diffusive case, which is inconsistent with market efficiency. In the sub-diffusive case the decay exponent β takes any value in [0, 1/2], and can be tuned to match the empirical value β ≈ 1/4. Numerical simulations confirm our theoretical results. Several extensions of the model are suggested. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Learning dynamics in social dilemmas

PubMed Central

Macy, Michael W.; Flache, Andreas

2002-01-01

The Nash equilibrium, the main solution concept in analytical game theory, cannot make precise predictions about the outcome of repeated mixed-motive games. Nor can it tell us much about the dynamics by which a population of players moves from one equilibrium to another. These limitations, along with concerns about the cognitive demands of forward-looking rationality, have motivated efforts to explore backward-looking alternatives to analytical game theory. Most of the effort has been invested in evolutionary models of population dynamics. We shift attention to a learning-theoretic alternative. Computational experiments with adaptive agents identify a fundamental solution concept for social dilemmas–−stochastic collusion–−based on a random walk from a self-limiting noncooperative equilibrium into a self-reinforcing cooperative equilibrium. However, we show that this solution is viable only within a narrow range of aspiration levels. Below the lower threshold, agents are pulled into a deficient equilibrium that is a stronger attractor than mutual cooperation. Above the upper threshold, agents are dissatisfied with mutual cooperation. Aspirations that adapt with experience (producing habituation to stimuli) do not gravitate into the window of viability; rather, they are the worst of both worlds. Habituation destabilizes cooperation and stabilizes defection. Results from the two-person problem suggest that applications to multiplex and embedded relationships will yield unexpected insights into the global dynamics of cooperation in social dilemmas. PMID:12011402

Agents of the Father's law in a society of brothers: A philosophic and psychoanalytic perspective on legitimate use of violence.

PubMed

Even-Tzur, Efrat; Hadar, Uri

This paper explores subjective processes of "Agents of Law" - individuals who the state grants the authority to use violence - and the dissonance stemming from the contradictory demands posed on them as legitimate users of violence despite the societal taboo against violence. A conceptual model will be offered based on two theoretical legs, Lacanian psychoanalysis and political theories of legitimacy. Specifically, psychoanalytic ideas would serve to examine unconscious processes, subject position and various identifications related to the question of "self-legitimacy" of Agents of Law. A central link between psychoanalysis and political thought is found in the image of the father and in the triad ruler-God-Father, which calls for an oedipal analysis. A psychoanalytic reading of two philosophical schools that elaborated on the question of legitimacy will be presented, and yield two analytic poles of a model for the understanding of possible subject positions of agents of Law: identification with a "Living Father" vs. identification with a "Dead Father". The psychoanalytic reading will shed light on the limitations of the philosophical perspectives in reflecting on the various (im)possible psychological positions of agents of Law. Finally, then, it will be shown how psychoanalysis helps finding words to characterize different nuances in the coping of agents of Law with the contradictory demands posed on them in an age in which God is dead, the father was murdered and the king was beheaded. Copyright © 2017 Elsevier Ltd. All rights reserved.

Controlled English to facilitate human/machine analytical processing

NASA Astrophysics Data System (ADS)

Braines, Dave; Mott, David; Laws, Simon; de Mel, Geeth; Pham, Tien

2013-06-01

Controlled English is a human-readable information representation format that is implemented using a restricted subset of the English language, but which is unambiguous and directly accessible by simple machine processes. We have been researching the capabilities of CE in a number of contexts, and exploring the degree to which a flexible and more human-friendly information representation format could aid the intelligence analyst in a multi-agent collaborative operational environment; especially in cases where the agents are a mixture of other human users and machine processes aimed at assisting the human users. CE itself is built upon a formal logic basis, but allows users to easily specify models for a domain of interest in a human-friendly language. In our research we have been developing an experimental component known as the "CE Store" in which CE information can be quickly and flexibly processed and shared between human and machine agents. The CE Store environment contains a number of specialized machine agents for common processing tasks and also supports execution of logical inference rules that can be defined in the same CE language. This paper outlines the basic architecture of this approach, discusses some of the example machine agents that have been developed, and provides some typical examples of the CE language and the way in which it has been used to support complex analytical tasks on synthetic data sources. We highlight the fusion of human and machine processing supported through the use of the CE language and CE Store environment, and show this environment with examples of highly dynamic extensions to the model(s) and integration between different user-defined models in a collaborative setting.

A Bayesian network meta-analysis for binary outcome: how to do it.

PubMed

Greco, Teresa; Landoni, Giovanni; Biondi-Zoccai, Giuseppe; D'Ascenzo, Fabrizio; Zangrillo, Alberto

2016-10-01

This study presents an overview of conceptual and practical issues of a network meta-analysis (NMA), particularly focusing on its application to randomised controlled trials with a binary outcome of interest. We start from general considerations on NMA to specifically appraise how to collect study data, structure the analytical network and specify the requirements for different models and parameter interpretations, with the ultimate goal of providing physicians and clinician-investigators a practical tool to understand pros and cons of NMA. Specifically, we outline the key steps, from the literature search to sensitivity analysis, necessary to perform a valid NMA of binomial data, exploiting Markov Chain Monte Carlo approaches. We also apply this analytical approach to a case study on the beneficial effects of volatile agents compared to total intravenous anaesthetics for surgery to further clarify the statistical details of the models, diagnostics and computations. Finally, datasets and models for the freeware WinBUGS package are presented for the anaesthetic agent example. © The Author(s) 2013.

Analytic War Plans: Adaptive Force-Employment Logic in the RAND Strategy Assessment System (RSAS)

DTIC Science & Technology

1990-07-01

Agents already mentioned, there is a Control Agent, which can act for the RSAS user in doing things the user would otherwise do interactively with the...single or series of connected operations to be carried out simultaneously or in succession . It is usually based upon stated assumptions and is the...which can act for the RSAS user in doing things the user would otherwise do interactively with the computer. 5 Control Agent has three modes of

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity

NASA Astrophysics Data System (ADS)

Sonubi, A.; Arcagni, A.; Stefani, S.; Ausloos, M.

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

Effects of competition and cooperation interaction between agents on networks in the presence of a market capacity.

PubMed

Sonubi, A; Arcagni, A; Stefani, S; Ausloos, M

2016-08-01

A network effect is introduced taking into account competition, cooperation, and mixed-type interaction among agents along a generalized Verhulst-Lotka-Volterra model. It is also argued that the presence of a market capacity undoubtedly enforces a definite limit on the agent's size growth. The state stability of triadic agents, i.e., the most basic network plaquette, is investigated analytically for possible scenarios, through a fixed-point analysis. It is discovered that: (i) market demand is only satisfied for full competition when one agent monopolizes the market; (ii) growth of agent size is encouraged in full cooperation; (iii) collaboration among agents to compete against one single agent may result in the disappearance of this single agent out of the market; and (iv) cooperating with two rivals may become a growth strategy for an intelligent agent.

Information-theoretic metamodel of organizational evolution

NASA Astrophysics Data System (ADS)

Sepulveda, Alfredo

2011-12-01

Social organizations are abstractly modeled by holarchies---self-similar connected networks---and intelligent complex adaptive multiagent systems---large networks of autonomous reasoning agents interacting via scaled processes. However, little is known of how information shapes evolution in such organizations, a gap that can lead to misleading analytics. The research problem addressed in this study was the ineffective manner in which classical model-predict-control methods used in business analytics attempt to define organization evolution. The purpose of the study was to construct an effective metamodel for organization evolution based on a proposed complex adaptive structure---the info-holarchy. Theoretical foundations of this study were holarchies, complex adaptive systems, evolutionary theory, and quantum mechanics, among other recently developed physical and information theories. Research questions addressed how information evolution patterns gleamed from the study's inductive metamodel more aptly explained volatility in organization. In this study, a hybrid grounded theory based on abstract inductive extensions of information theories was utilized as the research methodology. An overarching heuristic metamodel was framed from the theoretical analysis of the properties of these extension theories and applied to business, neural, and computational entities. This metamodel resulted in the synthesis of a metaphor for, and generalization of organization evolution, serving as the recommended and appropriate analytical tool to view business dynamics for future applications. This study may manifest positive social change through a fundamental understanding of complexity in business from general information theories, resulting in more effective management.

The LUE data model for representation of agents and fields

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2017-04-01

Traditionally, agents-based and field-based modelling environments use different data models to represent the state of information they manipulate. In agent-based modelling, involving the representation of phenomena as objects bounded in space and time, agents are often represented by classes, each of which represents a particular kind of agent and all its properties. Such classes can be used to represent entities like people, birds, cars and countries. In field-based modelling, involving the representation of the environment as continuous fields, fields are often represented by a discretization of space, using multidimensional arrays, each storing mostly a single attribute. Such arrays can be used to represent the elevation of the land-surface, the pH of the soil, or the population density in an area, for example. Representing a population of agents by class instances grouped in collections is an intuitive way of organizing information. A drawback, though, is that models in which class instances grouping properties are stored in collections are less efficient (execute slower) than models in which collections of properties are grouped. The field representation, on the other hand, is convenient for the efficient execution of models. Another drawback is that, because the data models used are so different, integrating agent-based and field-based models becomes difficult, since the model builder has to deal with multiple concepts, and often multiple modelling environments. With the development of the LUE data model [1] we aim at representing agents and fields within a single paradigm, by combining the advantages of the data models used in agent-based and field-based data modelling. This removes the barrier for writing integrated agent-based and field-based models. The resulting data model is intuitive to use and allows for efficient execution of models. LUE is both a high-level conceptual data model and a low-level physical data model. The LUE conceptual data model is a generalization of the data models used in agent-based and field-based modelling. The LUE physical data model [2] is an implementation of the LUE conceptual data model in HDF5. In our presentation we will provide details of our approach to organizing information about agents and fields. We will show examples of agent and field data represented by the conceptual and physical data model. References: [1] de Bakker, M.P., de Jong, K., Schmitz, O., Karssenberg, D., 2016. Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling and Software. http://dx.doi.org/10.1016/j.envsoft.2016.11.016 [2] de Jong, K., 2017. LUE source code. https://github.com/pcraster/lue

Noise-driven bias in the non-local voter model

NASA Astrophysics Data System (ADS)

Minors, Kevin; Rogers, Tim; Yates, Christian A.

2018-04-01

Is it more effective to have a strong influence over a small domain, or a weaker influence over a larger one? Here, we introduce and analyse an off-lattice generalisation of the voter model, in which the range and strength of agents' influence are control parameters. We consider both low- and high-density regimes and, using distinct mathematical approaches, derive analytical predictions for the evolution of agent densities. We find that, even when the agents are equally persuasive on average, those whose influence is wider but weaker have an overall noise-driven advantage allowing them to reliably dominate the entire population. We discuss the implications of our results and the potential of our model (or adaptations thereof) to improve the understanding of political campaign strategies and the evolution of disease.

Continuum models of cohesive stochastic swarms: The effect of motility on aggregation patterns

NASA Astrophysics Data System (ADS)

Hughes, Barry D.; Fellner, Klemens

2013-10-01

Mathematical models of swarms of moving agents with non-local interactions have many applications and have been the subject of considerable recent interest. For modest numbers of agents, cellular automata or related algorithms can be used to study such systems, but in the present work, instead of considering discrete agents, we discuss a class of one-dimensional continuum models, in which the agents possess a density ρ(x,t) at location x at time t. The agents are subject to a stochastic motility mechanism and to a global cohesive inter-agent force. The motility mechanisms covered include classical diffusion, nonlinear diffusion (which may be used to model, in a phenomenological way, volume exclusion or other short-range local interactions), and a family of linear redistribution operators related to fractional diffusion equations. A variety of exact analytic results are discussed, including equilibrium solutions and criteria for unimodality of equilibrium distributions, full time-dependent solutions, and transitions between asymptotic collapse and asymptotic escape. We address the behaviour of the system for diffusive motility in the low-diffusivity limit for both smooth and singular interaction potentials and show how this elucidates puzzling behaviour in fully deterministic non-local particle interaction models. We conclude with speculative remarks about extensions and applications of the models.

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

EpiK: A Knowledge Base for Epidemiological Modeling and Analytics of Infectious Diseases

DOE PAGES

Hasan, S. M. Shamimul; Fox, Edward A.; Bisset, Keith; ...

2017-11-06

Computational epidemiology seeks to develop computational methods to study the distribution and determinants of health-related states or events (including disease), and the application of this study to the control of diseases and other health problems. Recent advances in computing and data sciences have led to the development of innovative modeling environments to support this important goal. The datasets used to drive the dynamic models as well as the data produced by these models presents unique challenges owing to their size, heterogeneity and diversity. These datasets form the basis of effective and easy to use decision support and analytical environments. Asmore » a result, it is important to develop scalable data management systems to store, manage and integrate these datasets. In this paper, we develop EpiK—a knowledge base that facilitates the development of decision support and analytical environments to support epidemic science. An important goal is to develop a framework that links the input as well as output datasets to facilitate effective spatio-temporal and social reasoning that is critical in planning and intervention analysis before and during an epidemic. The data management framework links modeling workflow data and its metadata using a controlled vocabulary. The metadata captures information about storage, the mapping between the linked model and the physical layout, and relationships to support services. EpiK is designed to support agent-based modeling and analytics frameworks—aggregate models can be seen as special cases and are thus supported. We use semantic web technologies to create a representation of the datasets that encapsulates both the location and the schema heterogeneity. The choice of RDF as a representation language is motivated by the diversity and growth of the datasets that need to be integrated. A query bank is developed—the queries capture a broad range of questions that can be posed and answered during a typical case study pertaining to disease outbreaks. The queries are constructed using SPARQL Protocol and RDF Query Language (SPARQL) over the EpiK. EpiK can hide schema and location heterogeneity while efficiently supporting queries that span the computational epidemiology modeling pipeline: from model construction to simulation output. As a result, we show that the performance of benchmark queries varies significantly with respect to the choice of hardware underlying the database and resource description framework (RDF) engine.« less

Analysis of iodinated X-ray contrast agents in water samples by ion chromatography and inductively-coupled plasma mass spectrometry.

PubMed

Sacher, Frank; Raue, Brigitte; Brauch, Heinz-Jürgen

2005-08-26

In this paper, an analytical method for the determination of six iodinated X-ray contrast agents (amidotrizoic acid, iohexol, iomeprol, iopamidol, iopromide, and ioxitalamic acid), iodide, and iodate in water samples is presented. The method is based on a separation of the analytes by ion chromatography (IC) and a subsequent detection by inductively-coupled plasma mass spectrometry (ICP-MS). The method was optimised with respect to separation conditions (column type and eluent composition) and extensively validated. Without pre-concentration of the samples, limits of detection below 0.2 microg/l could be achieved whereby reproducibility was below 6% for all compounds under investigation.

Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets

NASA Astrophysics Data System (ADS)

Sornette, Didier; Zhou, Wei-Xing

2006-10-01

Following a long tradition of physicists who have noticed that the Ising model provides a general background to build realistic models of social interactions, we study a model of financial price dynamics resulting from the collective aggregate decisions of agents. This model incorporates imitation, the impact of external news and private information. It has the structure of a dynamical Ising model in which agents have two opinions (buy or sell) with coupling coefficients, which evolve in time with a memory of how past news have explained realized market returns. We study two versions of the model, which differ on how the agents interpret the predictive power of news. We show that the stylized facts of financial markets are reproduced only when agents are overconfident and mis-attribute the success of news to predict return to herding effects, thereby providing positive feedbacks leading to the model functioning close to the critical point. Our model exhibits a rich multifractal structure characterized by a continuous spectrum of exponents of the power law relaxation of endogenous bursts of volatility, in good agreement with previous analytical predictions obtained with the multifractal random walk model and with empirical facts.

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

Agent autonomy approach to probabilistic physics-of-failure modeling of complex dynamic systems with interacting failure mechanisms

NASA Astrophysics Data System (ADS)

Gromek, Katherine Emily

A novel computational and inference framework of the physics-of-failure (PoF) reliability modeling for complex dynamic systems has been established in this research. The PoF-based reliability models are used to perform a real time simulation of system failure processes, so that the system level reliability modeling would constitute inferences from checking the status of component level reliability at any given time. The "agent autonomy" concept is applied as a solution method for the system-level probabilistic PoF-based (i.e. PPoF-based) modeling. This concept originated from artificial intelligence (AI) as a leading intelligent computational inference in modeling of multi agents systems (MAS). The concept of agent autonomy in the context of reliability modeling was first proposed by M. Azarkhail [1], where a fundamentally new idea of system representation by autonomous intelligent agents for the purpose of reliability modeling was introduced. Contribution of the current work lies in the further development of the agent anatomy concept, particularly the refined agent classification within the scope of the PoF-based system reliability modeling, new approaches to the learning and the autonomy properties of the intelligent agents, and modeling interacting failure mechanisms within the dynamic engineering system. The autonomous property of intelligent agents is defined as agent's ability to self-activate, deactivate or completely redefine their role in the analysis. This property of agents and the ability to model interacting failure mechanisms of the system elements makes the agent autonomy fundamentally different from all existing methods of probabilistic PoF-based reliability modeling. 1. Azarkhail, M., "Agent Autonomy Approach to Physics-Based Reliability Modeling of Structures and Mechanical Systems", PhD thesis, University of Maryland, College Park, 2007.

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

ERIC Educational Resources Information Center

Snijders, Tom A. B.; Steglich, Christian E. G.

2015-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

Combining Advanced Turbulent Mixing and Combustion Models with Advanced Multi-Phase CFD Code to Simulate Detonation and Post-Detonation Bio-Agent Mixing and Destruction

DTIC Science & Technology

2017-10-01

perturbations in the energetic material to study their effects on the blast wave formation. The last case also makes use of the same PBX, however, the...configuration, Case A: Spore cloud located on the top of the charge at an angle 45 degree, Case B: Spore cloud located at an angle 45 degree from the charge...theoretical validation. The first is the Sedov case where the pressure decay and blast wave front are validated based on analytical solutions. In this test

Voter dynamics on an adaptive network with finite average connectivity

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Abhishek; Schmittmann, Beate

2009-03-01

We study a simple model for voter dynamics in a two-party system. The opinion formation process is implemented in a random network of agents in which interactions are not restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships, so that there is no history dependence in the model. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion and with opponents. Using simulations and analytic arguments, we determine the final steady states and the relaxation into these states for different system sizes. In contrast to earlier studies, the average connectivity (``degree'') of each agent is constant here, independent of the system size. This has significant consequences for the long-time behavior of the model.

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

Derivation of Markov processes that violate detailed balance

NASA Astrophysics Data System (ADS)

Lee, Julian

2018-03-01

Time-reversal symmetry of the microscopic laws dictates that the equilibrium distribution of a stochastic process must obey the condition of detailed balance. However, cyclic Markov processes that do not admit equilibrium distributions with detailed balance are often used to model systems driven out of equilibrium by external agents. I show that for a Markov model without detailed balance, an extended Markov model can be constructed, which explicitly includes the degrees of freedom for the driving agent and satisfies the detailed balance condition. The original cyclic Markov model for the driven system is then recovered as an approximation at early times by summing over the degrees of freedom for the driving agent. I also show that the widely accepted expression for the entropy production in a cyclic Markov model is actually a time derivative of an entropy component in the extended model. Further, I present an analytic expression for the entropy component that is hidden in the cyclic Markov model.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Tissue-based standoff biosensors for detecting chemical warfare agents

DOEpatents

Greenbaum, Elias; Sanders, Charlene A.

2003-11-18

A tissue-based, deployable, standoff air quality sensor for detecting the presence of at least one chemical or biological warfare agent, includes: a cell containing entrapped photosynthetic tissue, the cell adapted for analyzing photosynthetic activity of the entrapped photosynthetic tissue; means for introducing an air sample into the cell and contacting the air sample with the entrapped photosynthetic tissue; a fluorometer in operable relationship with the cell for measuring photosynthetic activity of the entrapped photosynthetic tissue; and transmitting means for transmitting analytical data generated by the fluorometer relating to the presence of at least one chemical or biological warfare agent in the air sample, the sensor adapted for deployment into a selected area.

Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania—Synthesis and Antibacterial Properties

PubMed Central

Svensson, Fredric G.; Agafonov, Alexander V.; Håkansson, Sebastian; Seisenbaeva, Gulaim A.

2018-01-01

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H2SO4. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus. It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents. PMID:29642486

Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania-Synthesis and Antibacterial Properties.

PubMed

Evdokimova, Olga L; Svensson, Fredric G; Agafonov, Alexander V; Håkansson, Sebastian; Seisenbaeva, Gulaim A; Kessler, Vadim G

2018-04-08

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H₂SO₄. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus . It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents.

Modeling the dynamical interaction between epidemics on overlay networks

NASA Astrophysics Data System (ADS)

Marceau, Vincent; Noël, Pierre-André; Hébert-Dufresne, Laurent; Allard, Antoine; Dubé, Louis J.

2011-08-01

Epidemics seldom occur as isolated phenomena. Typically, two or more viral agents spread within the same host population and may interact dynamically with each other. We present a general model where two viral agents interact via an immunity mechanism as they propagate simultaneously on two networks connecting the same set of nodes. By exploiting a correspondence between the propagation dynamics and a dynamical process performing progressive network generation, we develop an analytical approach that accurately captures the dynamical interaction between epidemics on overlay networks. The formalism allows for overlay networks with arbitrary joint degree distribution and overlap. To illustrate the versatility of our approach, we consider a hypothetical delayed intervention scenario in which an immunizing agent is disseminated in a host population to hinder the propagation of an undesirable agent (e.g., the spread of preventive information in the context of an emerging infectious disease).

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography.

PubMed

Delloye, Justin; Peeters, Dominique; Thomas, Isabelle

2015-01-01

In this paper, we aim at exploring how individual location decisions affect the shape of a growing city and, more precisely, how they may add up to a configuration that diverges from equilibrium configurations formulated ex-ante. To do so, we provide a two-sector city model merging a static equilibrium analysis with agent-based simulations. Results show that under strong agglomeration effects, urban development is monotonic and ends up with circular, monocentric long-term configurations. For low agglomeration effects however, elongated and multicentric urban configurations may emerge. The occurrence and underlying dynamics of these configurations are also discussed regarding commuting costs and the distance-decay of agglomeration economies between firms. To sum up, our paper warns urban planning policy makers against the difference that may stand between appropriate long-term perspectives, represented here by analytic equilibrium configurations, and short-term urban configurations, simulated here by a multi-agent system.

Analytical model for minority games with evolutionary learning

NASA Astrophysics Data System (ADS)

Campos, Daniel; Méndez, Vicenç; Llebot, Josep E.; Hernández, Germán A.

2010-06-01

In a recent work [D. Campos, J.E. Llebot, V. Méndez, Theor. Popul. Biol. 74 (2009) 16] we have introduced a biological version of the Evolutionary Minority Game that tries to reproduce the intraspecific competition for limited resources in an ecosystem. In comparison with the complex decision-making mechanisms used in standard Minority Games, only two extremely simple strategies ( juveniles and adults) are accessible to the agents. Complexity is introduced instead through an evolutionary learning rule that allows younger agents to learn taking better decisions. We find that this game shows many of the typical properties found for Evolutionary Minority Games, like self-segregation behavior or the existence of an oscillation phase for a certain range of the parameter values. However, an analytical treatment becomes much easier in our case, taking advantage of the simple strategies considered. Using a model consisting of a simple dynamical system, the phase diagram of the game (which differentiates three phases: adults crowd, juveniles crowd and oscillations) is reproduced.

Swimming against the mainstream: the early years from chilly tributary to transformative mainstream.

PubMed

Bandura, Albert

2004-06-01

This article traces the transformative paradigm shift in the theory and practice of personal change. Within a decade, new conceptual models, analytic methodologies and modes of treatment were created. Treatments were altered in the content, locus, and agents of change. This enterprising period also witnessed a sweeping shift in the public acceptance of behaviorally oriented treatments. The present article also analyzes the evolving theorizing and applications of social cognitive theory rooted in modeling, self-regulatory, and self-efficacy mechanisms of psychosocial change. This model of change is implemented from an agentic perspective to promote personal, institutional, and society-wide changes that address some of the most urgent global problems.

Quantitative Determination of NTA and Other Chelating Agents in Detergents by Potentiometric Titration with Copper Ion Selective Electrode.

PubMed

Ito, Sana; Morita, Masaki

2016-01-01

Quantitative analysis of nitrilotriacetate (NTA) in detergents by titration with Cu 2+ solution using a copper ion selective electrode was achieved. This method tolerates a wide range of pH and ingredients in detergents. In addition to NTA, other chelating agents, having relatively lower stability constants toward Cu 2+ , were also qualified with sufficient accuracy by this analytical method for model detergent formulations. The titration process was automated by automatic titrating systems available commercially.

The highly intelligent virtual agents for modeling financial markets

NASA Astrophysics Data System (ADS)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

Treesearch

Hsiao-Hsuan Wang; William Grant; Todd Swannack; Jianbang Gan; William Rogers; Tomasz Koralewski; James Miller; John W. Taylor Jr.

2011-01-01

We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Magnetic biosensors: Modelling and simulation.

PubMed

Nabaei, Vahid; Chandrawati, Rona; Heidari, Hadi

2018-04-30

In the past few years, magnetoelectronics has emerged as a promising new platform technology in various biosensors for detection, identification, localisation and manipulation of a wide spectrum of biological, physical and chemical agents. The methods are based on the exposure of the magnetic field of a magnetically labelled biomolecule interacting with a complementary biomolecule bound to a magnetic field sensor. This Review presents various schemes of magnetic biosensor techniques from both simulation and modelling as well as analytical and numerical analysis points of view, and the performance variations under magnetic fields at steady and nonstationary states. This is followed by magnetic sensors modelling and simulations using advanced Multiphysics modelling software (e.g. Finite Element Method (FEM) etc.) and home-made developed tools. Furthermore, outlook and future directions of modelling and simulations of magnetic biosensors in different technologies and materials are critically discussed. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Detection of warfare agents in liquid foods using the brine shrimp lethality assay.

PubMed

Lumor, Stephen E; Diez-Gonzalez, Francisco; Labuza, Theodore P

2011-01-01

The brine shrimp lethality assay (BSLA) was used for rapid and non-specific detection of biological and chemical warfare agents at concentrations considerably below that which will cause harm to humans. Warfare agents detected include T-2 toxin, trimethylsilyl cyanide, and commercially available pesticides such as dichlorvos, diazinon, dursban, malathion, and parathion. The assay was performed by introducing 50 μL of milk or orange juice contaminated with each analyte into vials containing 10 freshly hatched brine shrimp nauplii in seawater. This was incubated at 28 °C for 24 h, after which mortality was determined. Mortality was converted to probits and the LC(50) was determined for each analyte by plotting probits of mortality against analyte concentration (log(10)). Our findings were the following: (1) the lethal effects of toxins dissolved in milk were observed, with T-2 toxin being the most lethal and malathion being the least, (2) except for parathion, the dosage (based on LC(50)) of analyte in a cup of milk (200 mL) consumed by a 6-y-old (20 kg) was less than the respective published rat LD(50) values, and (3) the BSLA was only suitable for detecting toxins dissolved in orange juice if incubation time was reduced to 6 h. Our results support the application of the BSLA for routine, rapid, and non-specific prescreening of liquid foods for possible sabotage by an employee or an intentional bioterrorist act. Practical Application: The findings of this study strongly indicate that the brine shrimp lethality assay can be adapted for nonspecific detection of warfare agents or toxins in food at any point during food production and distribution.

Bridging the Gap between Human Judgment and Automated Reasoning in Predictive Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanfilippo, Antonio P.; Riensche, Roderick M.; Unwin, Stephen D.

2010-06-07

Events occur daily that impact the health, security and sustainable growth of our society. If we are to address the challenges that emerge from these events, anticipatory reasoning has to become an everyday activity. Strong advances have been made in using integrated modeling for analysis and decision making. However, a wider impact of predictive analytics is currently hindered by the lack of systematic methods for integrating predictive inferences from computer models with human judgment. In this paper, we present a predictive analytics approach that supports anticipatory analysis and decision-making through a concerted reasoning effort that interleaves human judgment and automatedmore » inferences. We describe a systematic methodology for integrating modeling algorithms within a serious gaming environment in which role-playing by human agents provides updates to model nodes and the ensuing model outcomes in turn influence the behavior of the human players. The approach ensures a strong functional partnership between human players and computer models while maintaining a high degree of independence and greatly facilitating the connection between model and game structures.« less

Review of methods used for identification of biothreat agents in environmental protection and human health aspects.

PubMed

Mirski, Tomasz; Bartoszcze, Michał; Bielawska-Drózd, Agata; Cieślik, Piotr; Michalski, Aleksander J; Niemcewicz, Marcin; Kocik, Janusz; Chomiczewski, Krzysztof

2014-01-01

Modern threats of bioterrorism force the need to develop methods for rapid and accurate identification of dangerous biological agents. Currently, there are many types of methods used in this field of studies that are based on immunological or genetic techniques, or constitute a combination of both methods (immuno-genetic). There are also methods that have been developed on the basis of physical and chemical properties of the analytes. Each group of these analytical assays can be further divided into conventional methods (e.g. simple antigen-antibody reactions, classical PCR, real-time PCR), and modern technologies (e.g. microarray technology, aptamers, phosphors, etc.). Nanodiagnostics constitute another group of methods that utilize the objects at a nanoscale (below 100 nm). There are also integrated and automated diagnostic systems, which combine different methods and allow simultaneous sampling, extraction of genetic material and detection and identification of the analyte using genetic, as well as immunological techniques.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

NASA Technical Reports Server (NTRS)

Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

2005-01-01

Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

[Problem of bioterrorism under modern conditions].

PubMed

Vorob'ev, A A; Boev, B V; Bondarenko, V M; Gintsburg, A L

2002-01-01

It is practically impossible to discuss the problem of bioterrorism (BT) and to develop effective programs of decreasing the losses and expenses suffered by the society from the BT acts without evaluation of the threat and prognosis of consequences based on research and empiric data. Stained international situation following the act of terrorism (attack on the USA) on September 11, 2001, makes the scenarios of the bacterial weapon use (the causative agents of plague, smallpox, anthrax, etc.) by international terrorists most probable. In this connection studies on the analysis and prognostication of the consequences of BT, including mathematical and computer modelling, are necessary. The authors present the results of initiative studies on the analysis and prognostication of the consequences of the hypothetical act of BT with the use of the smallpox causative agent in a city with the population of about 1,000,000 inhabitants. The analytical prognostic studies on the operative analysis and prognostication of the consequences of the BT act with the use of the smallpox causative agent has demonstrated that the mathematical (computer) model of the epidemic outbreak of smallpox is an effective instrument of calculation studies. Prognostic evaluations of the consequences of the act of BT under the conditions of different reaction of public health services (time of detection, interventions) have been obtained with the use of modelling. In addition, the computer model is necessary for training health specialists to react adequately to the acts of BT with the use of different kinds of bacteriological weapons.

Collective helping and bystander effects in coevolving helping networks.

PubMed

Jo, Hang-Hyun; Lee, Hyun Keun; Park, Hyunggyu

2010-06-01

We study collective helping behavior and bystander effects in a coevolving helping network model. A node and a link of the network represents an agent who renders or receives help and a friendly relation between agents, respectively. A helping trial of an agent depends on relations with other involved agents and its result (success or failure) updates the relation between the helper and the recipient. We study the network link dynamics and its steady states analytically and numerically. The full phase diagram is presented with various kinds of active and inactive phases and the nature of phase transitions are explored. We find various interesting bystander effects, consistent with the field study results, of which the underlying mechanism is proposed.

Duality in an asset exchange model for wealth distribution

NASA Astrophysics Data System (ADS)

Li, Jie; Boghosian, Bruce M.

2018-05-01

Asset exchange models are agent-based economic models with binary transactions. Previous investigations have augmented these models with mechanisms for wealth redistribution, quantified by a parameter χ, and for trading bias favoring wealthier agents, quantified by a parameter ζ. By deriving and analyzing a Fokker-Planck equation for a particular asset exchange model thus augmented, it has been shown that it exhibits a second-order phase transition at ζ / χ = 1, between regimes with and without partial wealth condensation. In the "subcritical" regime with ζ / χ < 1, all of the wealth is classically distributed; in the "supercritical" regime with ζ / χ > 1, a fraction 1 - χ / ζ of the wealth is condensed. Intuitively, one may associate the supercritical, wealth-condensed regime as reflecting the presence of "oligarchy," by which we mean that an infinitesimal fraction of the total agents hold a finite fraction of the total wealth in the continuum limit. In this paper, we further elucidate the phase behavior of this model - and hence of the generalized solutions of the Fokker-Planck equation that describes it - by demonstrating the existence of a remarkable symmetry between its supercritical and subcritical regimes in the steady-state. Noting that the replacement { ζ → χ , χ → ζ } , which clearly has the effect of inverting the order parameter ζ / χ, provides a one-to-one correspondence between the subcritical and supercritical states, we demonstrate that the wealth distribution of the subcritical state is identical to that of the corresponding supercritical state when the oligarchy is removed from the latter. We demonstrate this result analytically, both from the microscopic agent-level model and from its macroscopic Fokker-Planck description, as well as numerically. We argue that this symmetry is a kind of duality, analogous to the famous Kramers-Wannier duality between the subcritical and supercritical states of the Ising model, and to the Maldacena duality that underlies AdS/CFT theory.

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Data-driven agent-based modeling, with application to rooftop solar adoption

DOE PAGES

Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

2016-01-25

Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

Emergence of grouping in multi-resource minority game dynamics

NASA Astrophysics Data System (ADS)

Huang, Zi-Gang; Zhang, Ji-Qiang; Dong, Jia-Qi; Huang, Liang; Lai, Ying-Cheng

2012-10-01

Complex systems arising in a modern society typically have many resources and strategies available for their dynamical evolutions. To explore quantitatively the behaviors of such systems, we propose a class of models to investigate Minority Game (MG) dynamics with multiple strategies. In particular, agents tend to choose the least used strategies based on available local information. A striking finding is the emergence of grouping states defined in terms of distinct strategies. We develop an analytic theory based on the mean-field framework to understand the ``bifurcations'' of the grouping states. The grouping phenomenon has also been identified in the Shanghai Stock-Market system, and we discuss its prevalence in other real-world systems. Our work demonstrates that complex systems obeying the MG rules can spontaneously self-organize themselves into certain divided states, and our model represents a basic and general mathematical framework to address this kind of phenomena in social, economical and political systems.

Applications of agent-based modeling to nutrient movement Lake Michigan

EPA Science Inventory

As part of an ongoing project aiming to provide useful information for nearshore management (harmful algal blooms, nutrient loading), we explore the value of agent-based models in Lake Michigan. Agent-based models follow many individual “agents” moving through a simul...

The Agent-based Approach: A New Direction for Computational Models of Development.

ERIC Educational Resources Information Center

Schlesinger, Matthew; Parisi, Domenico

2001-01-01

Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

Preparation of wafer-level glass cavities by a low-cost chemical foaming process (CFP).

PubMed

Shang, Jintang; Chen, Boyin; Lin, Wei; Wong, Ching-Ping; Zhang, Di; Xu, Chao; Liu, Junwen; Huang, Qing-An

2011-04-21

A novel foaming process-chemical foaming process (CFP)-using foaming agents to fabricate wafer-level micro glass cavities including channels and bubbles was investigated. The process consists of the following steps sequentially: (1) shallow cavities were fabricated by a wet etching on a silicon wafer; (2) powders of a proper foaming agent were placed in a silicon cavity, named 'mother cavity', on the etched silicon surface; (3) the silicon cavities were sealed with a glass wafer by anodic bonding; (4) the bonded wafers were heated to above the softening point of the glass, and baked for several minutes, when the gas released by the decomposition of the foaming agent in the 'mother cavity' went into the other sealed interconnected silicon cavities to foam the softened glass into cylindrical channels named 'daughter channels', or spherical bubbles named 'son bubbles'. Results showed that wafer-level micro glass cavities with smooth wall surfaces were achieved successfully without contamination by the CFP. A model for the CFP was proposed to predict the final shape of the glass cavity. Experimental results corresponded with model predictions. The CFP provides a low-cost avenue to preparation of micro glass cavities of high quality for applications such as micro-reactors, micro total analysis systems (μTAS), analytical and bio-analytical applications, and MEMS packaging.

Graphene oxide-based dispersive solid-phase extraction combined with in situ derivatization and gas chromatography-mass spectrometry for the determination of acidic pharmaceuticals in water.

PubMed

Naing, Nyi Nyi; Li, Sam Fong Yau; Lee, Hian Kee

2015-12-24

A fast and low-cost sample preparation method of graphene based dispersive solid-phase extraction combined with gas chromatography-mass spectrometric (GC-MS) analysis, was developed. The procedure involves an initial extraction with water-immiscible organic solvent, followed by a rapid clean-up using amine functionalized reduced graphene oxide as sorbent. Simple and fast one-step in situ derivatization using trimethylphenylammonium hydroxide was subsequently applied on acidic pharmaceuticals serving as model analytes, ibuprofen, gemfibrozil, naproxen, ketoprofen and diclofenac, before GC-MS analysis. Extraction parameters affecting the derivatization and extraction efficiency such as volume of derivatization agent, effect of desorption solvent, effect of pH and effect of ionic strength were investigated. Under the optimum conditions, the method demonstrated good limits of detection ranging from 1 to 16ngL(-1), linearity (from 0.01 to 50 and 0.05 to 50μgL(-1), depending on the analytes) and satisfactory repeatability of extractions (relative standard deviations, below 13%, n=3). Copyright © 2015 Elsevier B.V. All rights reserved.

Available Resources | Division of Cancer Prevention

Cancer.gov

Preclinical pharmacology and efficacy studies Identification and evaluation of intermediate biomarkers Formulation optimization for enhanced bioavailability and clinical usefulness Analytical method development for investigational agents in bulk form and in biological fluids and tissues PK and PK-PD modeling to optimize dosing regimen Scale-up non-cGMP and cGMP production of

Advances in analytical technologies for environmental protection and public safety.

PubMed

Sadik, O A; Wanekaya, A K; Andreescu, S

2004-06-01

Due to the increased threats of chemical and biological agents of injury by terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat chemical and biochemical toxins. In addition to the right mix of policies and training of medical personnel on how to recognize symptoms of biochemical warfare agents, the major success in combating terrorism still lies in the prevention, early detection and the efficient and timely response using reliable analytical technologies and powerful therapies for minimizing the effects in the event of an attack. The public and regulatory agencies expect reliable methodologies and devices for public security. Today's systems are too bulky or slow to meet the "detect-to-warn" needs for first responders such as soldiers and medical personnel. This paper presents the challenges in monitoring technologies for warfare agents and other toxins. It provides an overview of how advances in environmental analytical methodologies could be adapted to design reliable sensors for public safety and environmental surveillance. The paths to designing sensors that meet the needs of today's measurement challenges are analyzed using examples of novel sensors, autonomous cell-based toxicity monitoring, 'Lab-on-a-Chip' devices and conventional environmental analytical techniques. Finally, in order to ensure that the public and legal authorities are provided with quality data to make informed decisions, guidelines are provided for assessing data quality and quality assurance using the United States Environmental Protection Agency (US-EPA) methodologies.

Demeter, persephone, and the search for emergence in agent-based models.

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Howe, T. R.; Collier, N. T.

2006-01-01

In Greek mythology, the earth goddess Demeter was unable to find her daughter Persephone after Persephone was abducted by Hades, the god of the underworld. Demeter is said to have embarked on a long and frustrating, but ultimately successful, search to find her daughter. Unfortunately, long and frustrating searches are not confined to Greek mythology. In modern times, agent-based modelers often face similar troubles when searching for agents that are to be to be connected to one another and when seeking appropriate target agents while defining agent behaviors. The result is a 'search for emergence' in that many emergent ormore » potentially emergent behaviors in agent-based models of complex adaptive systems either implicitly or explicitly require search functions. This paper considers a new nested querying approach to simplifying such agent-based modeling and multi-agent simulation search problems.« less

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

Reproducing Phenomenology of Peroxidation Kinetics via Model Optimization

NASA Astrophysics Data System (ADS)

Ruslanov, Anatole D.; Bashylau, Anton V.

2010-06-01

We studied mathematical modeling of lipid peroxidation using a biochemical model system of iron (II)-ascorbate-dependent lipid peroxidation of rat hepatocyte mitochondrial fractions. We found that antioxidants extracted from plants demonstrate a high intensity of peroxidation inhibition. We simplified the system of differential equations that describes the kinetics of the mathematical model to a first order equation, which can be solved analytically. Moreover, we endeavor to algorithmically and heuristically recreate the processes and construct an environment that closely resembles the corresponding natural system. Our results demonstrate that it is possible to theoretically predict both the kinetics of oxidation and the intensity of inhibition without resorting to analytical and biochemical research, which is important for cost-effective discovery and development of medical agents with antioxidant action from the medicinal plants.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Analysis of a variety of inorganic and organic additives in food products by ion-pairing liquid chromatography coupled to high-resolution mass spectrometry.

PubMed

Kaufmann, Anton; Widmer, Mirjam; Maden, Kathryn; Butcher, Patrick; Walker, Stephan

2018-03-05

A reversed-phase ion-pairing chromatographic method was developed for the detection and quantification of inorganic and organic anionic food additives. A single-stage high-resolution mass spectrometer (orbitrap ion trap, Orbitrap) was used to detect the accurate masses of the unfragmented analyte ions. The developed ion-pairing chromatography method was based on a dibutylamine/hexafluoro-2-propanol buffer. Dibutylamine can be charged to serve as a chromatographic ion-pairing agent. This ensures sufficient retention of inorganic and organic anions. Yet, unlike quaternary amines, it can be de-charged in the electrospray to prevent the formation of neutral analyte ion-pairing agent adducts. This process is significantly facilitated by the added hexafluoro-2-propanol. This approach permits the sensitive detection and quantification of additives like nitrate and mono-, di-, and triphosphate as well as citric acid, a number of artificial sweeteners like cyclamate and aspartame, flavor enhancers like glutamate, and preservatives like sorbic acid. This is a major advantage, since the currently used analytical methods as utilized in food safety laboratories are only capable in monitoring a few compounds or a particular category of food additives. Graphical abstract Deptotonation of ion pair agent in the electrospray interface.

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

Agent-based modeling of the spread of the 1918-1919 flu in three Canadian fur trading communities.

PubMed

O'Neil, Caroline A; Sattenspiel, Lisa

2010-01-01

Previous attempts to study the 1918-1919 flu in three small communities in central Manitoba have used both three-community population-based and single-community agent-based models. These studies identified critical factors influencing epidemic spread, but they also left important questions unanswered. The objective of this project was to design a more realistic agent-based model that would overcome limitations of earlier models and provide new insights into these outstanding questions. The new model extends the previous agent-based model to three communities so that results can be compared to those from the population-based model. Sensitivity testing was conducted, and the new model was used to investigate the influence of seasonal settlement and mobility patterns, the geographic heterogeneity of the observed 1918-1919 epidemic in Manitoba, and other questions addressed previously. Results confirm outcomes from the population-based model that suggest that (a) social organization and mobility strongly influence the timing and severity of epidemics and (b) the impact of the epidemic would have been greater if it had arrived in the summer rather than the winter. New insights from the model suggest that the observed heterogeneity among communities in epidemic impact was not unusual and would have been the expected outcome given settlement structure and levels of interaction among communities. Application of an agent-based computer simulation has helped to better explain observed patterns of spread of the 1918-1919 flu epidemic in central Manitoba. Contrasts between agent-based and population-based models illustrate the advantages of agent-based models for the study of small populations. © 2010 Wiley-Liss, Inc.

Unsilencing Critical Conversations in Social-Studies Teacher Education Using Agent-Based Modeling

ERIC Educational Resources Information Center

Hostetler, Andrew; Sengupta, Pratim; Hollett, Ty

2018-01-01

In this article, we argue that when complex sociopolitical issues such as ethnocentrism and racial segregation are represented as complex, emergent systems using agent-based computational models (in short agent-based models or ABMs), discourse about these representations can disrupt social studies teacher candidates' dispositions of teaching…

Noninvasive Biomonitoring Approaches to Determine Dosimetry and Risk Following Acute Chemical Exposure: Analysis of Lead or Organophosphate Insecticide in Saliva

DOE Office of Scientific and Technical Information (OSTI.GOV)

Timchalk, Chuck; Poet, Torka S.; Kousba, Ahmed A.

2004-04-01

There is a need to develop approaches for assessing risk associated with acute exposures to a broad-range of chemical agents and to rapidly determine the potential implications to human health. Non-invasive biomonitoring approaches are being developed using reliable portable analytical systems to quantitate dosimetry utilizing readily obtainable body fluids, such as saliva. Saliva has been used to evaluate a broad range of biomarkers, drugs, and environmental contaminants including heavy metals and pesticides. To advance the application of non-invasive biomonitoring a microfluidic/ electrochemical device has also been developed for the analysis of lead (Pb), using square wave anodic stripping voltammetry. Themore » system demonstrates a linear response over a broad concentration range (1 2000 ppb) and is capable of quantitating saliva Pb in rats orally administered acute doses of Pb-acetate. Appropriate pharmacokinetic analyses have been used to quantitate systemic dosimetry based on determination of saliva Pb concentrations. In addition, saliva has recently been used to quantitate dosimetry following exposure to the organophosphate insecticide chlorpyrifos in a rodent model system by measuring the major metabolite, trichloropyridinol, and saliva cholinesterase inhibition following acute exposures. These results suggest that technology developed for non-invasive biomonitoring can provide a sensitive, and portable analytical tool capable of assessing exposure and risk in real-time. By coupling these non-invasive technologies with pharmacokinetic modeling it is feasible to rapidly quantitate acute exposure to a broad range of chemical agents. In summary, it is envisioned that once fully developed, these monitoring and modeling approaches will be useful for accessing acute exposure and health risk.« less

Brief introductory guide to agent-based modeling and an illustration from urban health research.

PubMed

Auchincloss, Amy H; Garcia, Leandro Martin Totaro

2015-11-01

There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

Brief introductory guide to agent-based modeling and an illustration from urban health research

PubMed Central

Auchincloss, Amy H.; Garcia, Leandro Martin Totaro

2017-01-01

There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation. PMID:26648364

A technology path to tactical agent-based modeling

NASA Astrophysics Data System (ADS)

James, Alex; Hanratty, Timothy P.

2017-05-01

Wargaming is a process of thinking through and visualizing events that could occur during a possible course of action. Over the past 200 years, wargaming has matured into a set of formalized processes. One area of growing interest is the application of agent-based modeling. Agent-based modeling and its additional supporting technologies has potential to introduce a third-generation wargaming capability to the Army, creating a positive overmatch decision-making capability. In its simplest form, agent-based modeling is a computational technique that helps the modeler understand and simulate how the "whole of a system" responds to change over time. It provides a decentralized method of looking at situations where individual agents are instantiated within an environment, interact with each other, and empowered to make their own decisions. However, this technology is not without its own risks and limitations. This paper explores a technology roadmap, identifying research topics that could realize agent-based modeling within a tactical wargaming context.

A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

PubMed Central

Parker, Jon; Epstein, Joshua M.

2013-01-01

The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

An extensible simulation environment and movement metrics for testing walking behavior in agent-based models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul M. Torrens; Atsushi Nara; Xun Li

2012-01-01

Human movement is a significant ingredient of many social, environmental, and technical systems, yet the importance of movement is often discounted in considering systems complexity. Movement is commonly abstracted in agent-based modeling (which is perhaps the methodological vehicle for modeling complex systems), despite the influence of movement upon information exchange and adaptation in a system. In particular, agent-based models of urban pedestrians often treat movement in proxy form at the expense of faithfully treating movement behavior with realistic agency. There exists little consensus about which method is appropriate for representing movement in agent-based schemes. In this paper, we examine popularly-usedmore » methods to drive movement in agent-based models, first by introducing a methodology that can flexibly handle many representations of movement at many different scales and second, introducing a suite of tools to benchmark agent movement between models and against real-world trajectory data. We find that most popular movement schemes do a relatively poor job of representing movement, but that some schemes may well be 'good enough' for some applications. We also discuss potential avenues for improving the representation of movement in agent-based frameworks.« less

Agent-Based Modeling in Public Health: Current Applications and Future Directions.

PubMed

Tracy, Melissa; Cerdá, Magdalena; Keyes, Katherine M

2018-04-01

Agent-based modeling is a computational approach in which agents with a specified set of characteristics interact with each other and with their environment according to predefined rules. We review key areas in public health where agent-based modeling has been adopted, including both communicable and noncommunicable disease, health behaviors, and social epidemiology. We also describe the main strengths and limitations of this approach for questions with public health relevance. Finally, we describe both methodologic and substantive future directions that we believe will enhance the value of agent-based modeling for public health. In particular, advances in model validation, comparisons with other causal modeling procedures, and the expansion of the models to consider comorbidity and joint influences more systematically will improve the utility of this approach to inform public health research, practice, and policy.

Competitive advantage for multiple-memory strategies in an artificial market

NASA Astrophysics Data System (ADS)

Mitman, Kurt E.; Choe, Sehyo C.; Johnson, Neil F.

2005-05-01

We consider a simple binary market model containing N competitive agents. The novel feature of our model is that it incorporates the tendency shown by traders to look for patterns in past price movements over multiple time scales, i.e. multiple memory-lengths. In the regime where these memory-lengths are all small, the average winnings per agent exceed those obtained for either (1) a pure population where all agents have equal memory-length, or (2) a mixed population comprising sub-populations of equal-memory agents with each sub-population having a different memory-length. Agents who consistently play strategies of a given memory-length, are found to win more on average -- switching between strategies with different memory lengths incurs an effective penalty, while switching between strategies of equal memory does not. Agents employing short-memory strategies can outperform agents using long-memory strategies, even in the regime where an equal-memory system would have favored the use of long-memory strategies. Using the many-body 'Crowd-Anticrowd' theory, we obtain analytic expressions which are in good agreement with the observed numerical results. In the context of financial markets, our results suggest that multiple-memory agents have a better chance of identifying price patterns of unknown length and hence will typically have higher winnings.

The ultimatum game: Discrete vs. continuous offers

NASA Astrophysics Data System (ADS)

Dishon-Berkovits, Miriam; Berkovits, Richard

2014-09-01

In many experimental setups in social-sciences, psychology and economy the subjects are requested to accept or dispense monetary compensation which is usually given in discrete units. Using computer and mathematical modeling we show that in the framework of studying the dynamics of acceptance of proposals in the ultimatum game, the long time dynamics of acceptance of offers in the game are completely different for discrete vs. continuous offers. For discrete values the dynamics follow an exponential behavior. However, for continuous offers the dynamics are described by a power-law. This is shown using an agent based computer simulation as well as by utilizing an analytical solution of a mean-field equation describing the model. These findings have implications to the design and interpretation of socio-economical experiments beyond the ultimatum game.

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson's arms race model.

PubMed

Riaz, Faisal; Niazi, Muaz A

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson's arms race model has also been presented. The performance of the proposed social agent has been validated at two levels-firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme.

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson’s arms race model

PubMed Central

Niazi, Muaz A.

2017-01-01

This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. Exploratory Agent Based Modeling (EABM) level of the Cognitive Agent Based Computing (CABC) framework has been utilized to design the proposed social agent. Furthermore, to emulate the functionality of mentalizing and mirroring modules of proposed social agent, a tailored mathematical model of the Richardson’s arms race model has also been presented. The performance of the proposed social agent has been validated at two levels–firstly it has been simulated using NetLogo, a standard agent-based modeling tool and also, at a practical level using a prototype AV. The simulation results have confirmed that the proposed social agent-based collision avoidance strategy is 78.52% more efficient than Random walk based collision avoidance strategy in congested flock-like topologies. Whereas practical results have confirmed that the proposed scheme can avoid rear end and lateral collisions with the efficiency of 99.876% as compared with the IEEE 802.11n-based existing state of the art mirroring neuron-based collision avoidance scheme. PMID:29040294

Multi-gas interaction modeling on decorated semiconductor interfaces: A novel Fermi distribution-based response isotherm and the inverse hard/soft acid/base concept

NASA Astrophysics Data System (ADS)

Laminack, William; Gole, James

2015-12-01

A unique MEMS/NEMS approach is presented for the modeling of a detection platform for mixed gas interactions. Mixed gas analytes interact with nanostructured decorating metal oxide island sites supported on a microporous silicon substrate. The Inverse Hard/Soft acid/base (IHSAB) concept is used to assess a diversity of conductometric responses for mixed gas interactions as a function of these nanostructured metal oxides. The analyte conductometric responses are well represented using a combination diffusion/absorption-based model for multi-gas interactions where a newly developed response absorption isotherm, based on the Fermi distribution function is applied. A further coupling of this model with the IHSAB concept describes the considerations in modeling of multi-gas mixed analyte-interface, and analyte-analyte interactions. Taking into account the molecular electronic interaction of both the analytes with each other and an extrinsic semiconductor interface we demonstrate how the presence of one gas can enhance or diminish the reversible interaction of a second gas with the extrinsic semiconductor interface. These concepts demonstrate important considerations in the array-based formats for multi-gas sensing and its applications.

Secondary electrospray ionization of complex vapor mixtures. Theoretical and experimental approach.

PubMed

Vidal-de-Miguel, Guillermo; Herrero, Ana

2012-06-01

In secondary electrospray ionization (SESI) systems, gaseous analytes exposed to an electrospray plume become ionized after charge is transferred from the charging electrosprayed particles (the charging agent) to the vapor species. Currently available SESI models are valid for simplified systems having only one type of electrosprayed species, which ionizes only one single vapor species, and for the limit of low vapor concentration. More realistic models require considering other effects. Here we develop a theoretical model that accounts for the effects of high vapor concentration, saturation effects, interferences between different vapor species, and electrosprays producing different types of species from the liquid phase. In spite of the relatively high complexity of the problem, we find simple relations between the different ionic species concentrations that hold independently of the particular ion source configuration. Our model suggests that an ideal SESI system should use highly concentrated charging agents composed preferably of only one dominating species with low mobility. Experimental measurements with a MeOH-H(2)O-NH(3) electrospray and a mixture of fatty acids and lactic acid served to test the theory, which gives good qualitative results. These results also suggest that the SESI ionization mechanism is primarily based on ions rather than on charged droplets.

Master equation for a kinetic model of a trading market and its analytic solution

NASA Astrophysics Data System (ADS)

Chatterjee, Arnab; Chakrabarti, Bikas K.; Stinchcombe, Robin B.

2005-08-01

We analyze an ideal-gas-like model of a trading market with quenched random saving factors for its agents and show that the steady state income (m) distribution P(m) in the model has a power law tail with Pareto index ν exactly equal to unity, confirming the earlier numerical studies on this model. The analysis starts with the development of a master equation for the time development of P(m) . Precise solutions are then obtained in some special cases.

Master equation for a kinetic model of a trading market and its analytic solution.

PubMed

Chatterjee, Arnab; Chakrabarti, Bikas K; Stinchcombe, Robin B

2005-08-01

We analyze an ideal-gas-like model of a trading market with quenched random saving factors for its agents and show that the steady state income (m) distribution P(m) in the model has a power law tail with Pareto index nu exactly equal to unity, confirming the earlier numerical studies on this model. The analysis starts with the development of a master equation for the time development of P(m) . Precise solutions are then obtained in some special cases.

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

Metal-Organic Framework Modified Glass Substrate for Analysis of Highly Volatile Chemical Warfare Agents by Paper Spray Mass Spectrometry.

PubMed

Dhummakupt, Elizabeth S; Carmany, Daniel O; Mach, Phillip M; Tovar, Trenton M; Ploskonka, Ann M; Demond, Paul S; DeCoste, Jared B; Glaros, Trevor

2018-03-07

Paper spray mass spectrometry has been shown to successfully analyze chemical warfare agent (CWA) simulants. However, due to the volatility differences between the simulants and real G-series (i.e., sarin, soman) CWAs, analysis from an untreated paper substrate proved difficult. To extend the analytical lifetime of these G-agents, metal-organic frameworks (MOFs) were successfully integrated onto the paper spray substrates to increase adsorption and desorption. In this study, several MOFs and nanoparticles were tested to extend the analytical lifetimes of sarin, soman, and cyclosarin on paper spray substrates. It was found that the addition of either UiO-66 or HKUST-1 to the paper substrate increased the analytical lifetime of the G-agents from less than 5 min detectability to at least 50 min.

Exploring the Use of Computer Simulations in Unraveling Research and Development Governance Problems

NASA Technical Reports Server (NTRS)

Balaban, Mariusz A.; Hester, Patrick T.

2012-01-01

Understanding Research and Development (R&D) enterprise relationships and processes at a governance level is not a simple task, but valuable decision-making insight and evaluation capabilities can be gained from their exploration through computer simulations. This paper discusses current Modeling and Simulation (M&S) methods, addressing their applicability to R&D enterprise governance. Specifically, the authors analyze advantages and disadvantages of the four methodologies used most often by M&S practitioners: System Dynamics (SO), Discrete Event Simulation (DES), Agent Based Modeling (ABM), and formal Analytic Methods (AM) for modeling systems at the governance level. Moreover, the paper describes nesting models using a multi-method approach. Guidance is provided to those seeking to employ modeling techniques in an R&D enterprise for the purposes of understanding enterprise governance. Further, an example is modeled and explored for potential insight. The paper concludes with recommendations regarding opportunities for concentration of future work in modeling and simulating R&D governance relationships and processes.

Tricritical points in a Vicsek model of self-propelled particles with bounded confidence

NASA Astrophysics Data System (ADS)

Romensky, Maksym; Lobaskin, Vladimir; Ihle, Thomas

2014-12-01

We study the orientational ordering in systems of self-propelled particles with selective interactions. To introduce the selectivity we augment the standard Vicsek model with a bounded-confidence collision rule: a given particle only aligns to neighbors who have directions quite similar to its own. Neighbors whose directions deviate more than a fixed restriction angle α are ignored. The collective dynamics of this system is studied by agent-based simulations and kinetic mean-field theory. We demonstrate that the reduction of the restriction angle leads to a critical noise amplitude decreasing monotonically with that angle, turning into a power law with exponent 3/2 for small angles. Moreover, for small system sizes we show that upon decreasing the restriction angle, the kind of the transition to polar collective motion changes from continuous to discontinuous. Thus, an apparent tricritical point with different scaling laws is identified and calculated analytically. We investigate the shifting and vanishing of this point due to the formation of density bands as the system size is increased. Agent-based simulations in small systems with large particle velocities show excellent agreement with the kinetic theory predictions. We also find that at very small interaction angles, the polar ordered phase becomes unstable with respect to the apolar phase. We derive analytical expressions for the dependence of the threshold noise on the restriction angle. We show that the mean-field kinetic theory also permits stationary nematic states below a restriction angle of 0.681 π . We calculate the critical noise, at which the disordered state bifurcates to a nematic state, and find that it is always smaller than the threshold noise for the transition from disorder to polar order. The disordered-nematic transition features two tricritical points: At low and high restriction angle, the transition is discontinuous but continuous at intermediate α . We generalize our results to systems that show fragmentation into more than two groups and obtain scaling laws for the transition lines and the corresponding tricritical points. A numerical method to evaluate the nonlinear Fredholm integral equation for the stationary distribution function is also presented. This method is shown to give excellent agreement with agent-based simulations, even in strongly ordered systems at noise values close to zero.

Evolution and Extinction Dynamics in Rugged Fitness Landscapes

NASA Astrophysics Data System (ADS)

Sibani, Paolo; Brandt, Michael; Alstrøm, Preben

After an introductory section summarizing the paleontological data and some of their theoretical descriptions, we describe the "reset" model and its (in part analytically soluble) mean field version, which have been briefly introduced in Letters.1,2 Macroevolution is considered as a problem of stochastic dynamics in a system with many competing agents. Evolutionary events (speciations and extinctions) are triggered by fitness records found by random exploration of the agents' fitness landscapes. As a consequence, the average fitness in the system increases logarithmically with time, while the rate of extinction steadily decreases. This non-stationary dynamics is studied by numerical simulations and, in a simpler mean field version, analytically. We also consider the effect of externally added "mass" extinctions. The predictions for various quantities of paleontological interest (life-time distribution, distribution of event sizes and behavior of the rate of extinction) are robust and in good agreement with available data.

A Cybernetic Approach to the Modeling of Agent Communities

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Karlin, Jay

2000-01-01

In an earlier paper [1] examples of agent technology in a NASA context were presented. Both groundbased and space-based applications were addressed. This paper continues the discussion of one aspect of the Goddard Space Flight Center's continuing efforts to develop a community of agents that can support both ground-based and space-based systems autonomy. The paper focuses on an approach to agent-community modeling based on the theory of viable systems developed by Stafford Beer. It gives the status of an initial attempt to capture some of the agent-community behaviors in a viable system context. This paper is expository in nature and focuses on a discussion of the modeling of some of the underlying concepts and infrastructure that will serve as the basis of more detailed investigative work into the behavior of agent communities. The paper is organized as follows. First, a general introduction to agent community requirements is presented. Secondly, a brief introduction to the cybernetic concept of a viable system is given. This concept forms the foundation of the modeling approach. Then the concept of an agent community is modeled in the cybernetic context.

Simulating cancer growth with multiscale agent-based modeling.

PubMed

Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

2015-02-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Money creation process in a random redistribution model

NASA Astrophysics Data System (ADS)

Chen, Siyan; Wang, Yougui; Li, Keqiang; Wu, Jinshan

2014-01-01

In this paper, the dynamical process of money creation in a random exchange model with debt is investigated. The money creation kinetics are analyzed by both the money-transfer matrix method and the diffusion method. From both approaches, we attain the same conclusion: the source of money creation in the case of random exchange is the agents with neither money nor debt. These analytical results are demonstrated by computer simulations.

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

NASA Technical Reports Server (NTRS)

Kao, David; Kramer, Marc; Chaderjian, Neal

2005-01-01

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

Agent-based model for rural-urban migration: A dynamic consideration

NASA Astrophysics Data System (ADS)

Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

2015-10-01

This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

Development of Mechanistic Reasoning and Multilevel Explanations of Ecology in Third Grade Using Agent-Based Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim; Farris, Amy Voss; Satabdi, Basu

2016-01-01

In this paper, we present a third-grade ecology learning environment that integrates two forms of modeling--embodied modeling and agent-based modeling (ABMs)--through the generation of mathematical representations that are common to both forms of modeling. The term "agent" in the context of ABMs indicates individual computational objects…

Infrared differential-absorption Mueller matrix spectroscopy and neural network-based data fusion for biological aerosol standoff detection.

PubMed

Carrieri, Arthur H; Copper, Jack; Owens, David J; Roese, Erik S; Bottiger, Jerold R; Everly, Robert D; Hung, Kevin C

2010-01-20

An active spectrophotopolarimeter sensor and support system were developed for a military/civilian defense feasibility study concerning the identification and standoff detection of biological aerosols. Plumes of warfare agent surrogates gamma-irradiated Bacillus subtilis and chicken egg white albumen (analytes), Arizona road dust (terrestrial interferent), water mist (atmospheric interferent), and talcum powders (experiment controls) were dispersed inside windowless chambers and interrogated by multiple CO(2) laser beams spanning 9.1-12.0 microm wavelengths (lambda). Molecular vibration and vibration-rotation activities by the subject analyte are fundamentally strong within this "fingerprint" middle infrared spectral region. Distinct polarization-modulations of incident irradiance and backscatter radiance of tuned beams generate the Mueller matrix (M) of subject aerosol. Strings of all 15 normalized elements {M(ij)(lambda)/M(11)(lambda)}, which completely describe physical and geometric attributes of the aerosol particles, are input fields for training hybrid Kohonen self-organizing map feed-forward artificial neural networks (ANNs). The properly trained and validated ANN model performs pattern recognition and type-classification tasks via internal mappings. A typical ANN that mathematically clusters analyte, interferent, and control aerosols with nil overlap of species is illustrated, including sensitivity analysis of performance.

A genetic algorithm-based job scheduling model for big data analytics.

PubMed

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

Going beyond the unitary curve: incorporating richer cognition into agent-based water resources models

NASA Astrophysics Data System (ADS)

Kock, B. E.

2008-12-01

The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.

Multi-issue Agent Negotiation Based on Fairness

NASA Astrophysics Data System (ADS)

Zuo, Baohe; Zheng, Sue; Wu, Hong

Agent-based e-commerce service has become a hotspot now. How to make the agent negotiation process quickly and high-efficiently is the main research direction of this area. In the multi-issue model, MAUT(Multi-attribute Utility Theory) or its derived theory usually consider little about the fairness of both negotiators. This work presents a general model of agent negotiation which considered the satisfaction of both negotiators via autonomous learning. The model can evaluate offers from the opponent agent based on the satisfaction degree, learn online to get the opponent's knowledge from interactive instances of history and negotiation of this time, make concessions dynamically based on fair object. Through building the optimal negotiation model, the bilateral negotiation achieved a higher efficiency and fairer deal.

Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

PubMed

de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

2016-03-01

Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

Agent Model Development for Assessing Climate-Induced Geopolitical Instability.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boslough, Mark B.; Backus, George A.

2005-12-01

We present the initial stages of development of new agent-based computational methods to generate and test hypotheses about linkages between environmental change and international instability. This report summarizes the first year's effort of an originally proposed three-year Laboratory Directed Research and Development (LDRD) project. The preliminary work focused on a set of simple agent-based models and benefited from lessons learned in previous related projects and case studies of human response to climate change and environmental scarcity. Our approach was to define a qualitative model using extremely simple cellular agent models akin to Lovelock's Daisyworld and Schelling's segregation model. Such modelsmore » do not require significant computing resources, and users can modify behavior rules to gain insights. One of the difficulties in agent-based modeling is finding the right balance between model simplicity and real-world representation. Our approach was to keep agent behaviors as simple as possible during the development stage (described herein) and to ground them with a realistic geospatial Earth system model in subsequent years. This work is directed toward incorporating projected climate data--including various C02 scenarios from the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report--and ultimately toward coupling a useful agent-based model to a general circulation model.3« less

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

Research on monocentric model of urbanization by agent-based simulation

NASA Astrophysics Data System (ADS)

Xue, Ling; Yang, Kaizhong

2008-10-01

Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

Discretized kinetic theory on scale-free networks

NASA Astrophysics Data System (ADS)

Bertotti, Maria Letizia; Modanese, Giovanni

2016-10-01

The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

Role of optimization in the human dynamics of task execution

NASA Astrophysics Data System (ADS)

Cajueiro, Daniel O.; Maldonado, Wilfredo L.

2008-03-01

In order to explain the empirical evidence that the dynamics of human activity may not be well modeled by Poisson processes, a model based on queuing processes was built in the literature [A. L. Barabasi, Nature (London) 435, 207 (2005)]. The main assumption behind that model is that people execute their tasks based on a protocol that first executes the high priority item. In this context, the purpose of this paper is to analyze the validity of that hypothesis assuming that people are rational agents that make their decisions in order to minimize the cost of keeping nonexecuted tasks on the list. Therefore, we build and analytically solve a dynamic programming model with two priority types of tasks and show that the validity of this hypothesis depends strongly on the structure of the instantaneous costs that a person has to face if a given task is kept on the list for more than one period. Moreover, one interesting finding is that in one of the situations the protocol used to execute the tasks generates complex one-dimensional dynamics.

Greedy algorithms and Zipf laws

NASA Astrophysics Data System (ADS)

Moran, José; Bouchaud, Jean-Philippe

2018-04-01

We consider a simple model of firm/city/etc growth based on a multi-item criterion: whenever entity B fares better than entity A on a subset of M items out of K, the agent originally in A moves to B. We solve the model analytically in the cases K  =  1 and . The resulting stationary distribution of sizes is generically a Zipf-law provided M  >  K/2. When , no selection occurs and the size distribution remains thin-tailed. In the special case M  =  K, one needs to regularize the problem by introducing a small ‘default’ probability ϕ. We find that the stationary distribution has a power-law tail that becomes a Zipf-law when . The approach to the stationary state can also be characterized, with strong similarities with a simple ‘aging’ model considered by Barrat and Mézard.

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

NASA Astrophysics Data System (ADS)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach.

PubMed

Laghari, Samreen; Niazi, Muaz A

2016-01-01

Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach.

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

PubMed

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Choosing Fitness-Enhancing Innovations Can Be Detrimental under Fluctuating Environments

PubMed Central

Xue, Julian Z.; Costopoulos, Andre; Guichard, Frederic

2011-01-01

The ability to predict the consequences of one's behavior in a particular environment is a mechanism for adaptation. In the absence of any cost to this activity, we might expect agents to choose behaviors that maximize their fitness, an example of directed innovation. This is in contrast to blind mutation, where the probability of becoming a new genotype is independent of the fitness of the new genotypes. Here, we show that under environments punctuated by rapid reversals, a system with both genetic and cultural inheritance should not always maximize fitness through directed innovation. This is because populations highly accurate at selecting the fittest innovations tend to over-fit the environment during its stable phase, to the point that a rapid environmental reversal can cause extinction. A less accurate population, on the other hand, can track long term trends in environmental change, keeping closer to the time-average of the environment. We use both analytical and agent-based models to explore when this mechanism is expected to occur. PMID:22125601

On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography

PubMed Central

Delloye, Justin; Peeters, Dominique; Thomas, Isabelle

2015-01-01

In this paper, we aim at exploring how individual location decisions affect the shape of a growing city and, more precisely, how they may add up to a configuration that diverges from equilibrium configurations formulated ex-ante. To do so, we provide a two-sector city model merging a static equilibrium analysis with agent-based simulations. Results show that under strong agglomeration effects, urban development is monotonic and ends up with circular, monocentric long-term configurations. For low agglomeration effects however, elongated and multicentric urban configurations may emerge. The occurrence and underlying dynamics of these configurations are also discussed regarding commuting costs and the distance-decay of agglomeration economies between firms. To sum up, our paper warns urban planning policy makers against the difference that may stand between appropriate long-term perspectives, represented here by analytic equilibrium configurations, and short-term urban configurations, simulated here by a multi-agent system. PMID:26308858

Study of disulfide reduction and alkyl chloroformate derivatization of plasma sulfur amino acids using gas chromatography-mass spectrometry.

PubMed

Svagera, Zdeněk; Hanzlíková, Dagmar; Simek, Petr; Hušek, Petr

2012-03-01

Four disulfide-reducing agents, dithiothreitol (DTT), 2,3-dimercaptopropanesulfonate (DMPS), and the newly tested 2-mercaptoethanesulfonate (MESNA) and Tris(hydroxypropyl)phosphine (THP), were investigated in detail for release of sulfur amino acids in human plasma. After protein precipitation with trichloroacetic acid (TCA), the plasma supernatant was treated with methyl, ethyl, or propyl chloroformate via the well-proven derivatization-extraction technique and the products were subjected to gas chromatographic-mass spectrometric (GC-MS) analysis. All the tested agents proved to be rapid and effective reducing agents for the assay of plasma thiols. When compared with DTT, the novel reducing agents DMPS, MESNA, and THP provided much cleaner extracts and improved analytical performance. Quantification of homocysteine, cysteine, and methionine was performed using their deuterated analogues, whereas other analytes were quantified by means of 4-chlorophenylalanine. Precise and reliable assay of all examined analytes was achieved, irrespective of the chloroformate reagent used. Average relative standard deviations at each analyte level were ≤6%, quantification limits were 0.1-0.2 μmol L(-1), recoveries were 94-121%, and linearity was over three orders of magnitude (r(2) equal to 0.997-0.998). Validation performed with the THP agent and propyl chloroformate derivatization demonstrated the robustness and reliability of this simple sample-preparation methodology.

Little by Little Does the Trick: Design and Construction of a Discrete Event Agent-Based Simulation Framework

DTIC Science & Technology

2007-12-01

model. Finally, we build a small agent-based model using the component architecture to demonstrate the library’s functionality. 15. NUMBER OF...and a Behavioral model. Finally, we build a small agent-based model using the component architecture to demonstrate the library’s functionality...prototypes an architectural design which is generalizable, reusable, and extensible. We have created an initial set of model elements that demonstrate

The fractional volatility model: An agent-based interpretation

NASA Astrophysics Data System (ADS)

Vilela Mendes, R.

2008-06-01

Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

A place for agent-based models. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

NASA Astrophysics Data System (ADS)

Barbaro, Alethea

2015-03-01

Agent-based models have been widely applied in theoretical ecology to explain migrations and other collective animal movements [2,5,8]. As D'Orsogna and Perc have expertly highlighted in [6], the recent emergence of crime modeling has opened another interesting avenue for mathematical investigation. The area of crime modeling is particularly suited to agent-based models, because these models offer a great deal of flexibility within the model and also ease of communication among criminologist, law enforcement and modelers.

Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach

PubMed Central

Senior, Alistair M.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

2016-01-01

Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments. PMID:26858671

Nine-analyte detection using an array-based biosensor

NASA Technical Reports Server (NTRS)

Taitt, Chris Rowe; Anderson, George P.; Lingerfelt, Brian M.; Feldstein, s. Mark. J.; Ligler, Frances S.

2002-01-01

A fluorescence-based multianalyte immunosensor has been developed for simultaneous analysis of multiple samples. While the standard 6 x 6 format of the array sensor has been used to analyze six samples for six different analytes, this same format has the potential to allow a single sample to be tested for 36 different agents. The method described herein demonstrates proof of principle that the number of analytes detectable using a single array can be increased simply by using complementary mixtures of capture and tracer antibodies. Mixtures were optimized to allow detection of closely related analytes without significant cross-reactivity. Following this facile modification of patterning and assay procedures, the following nine targets could be detected in a single 3 x 3 array: Staphylococcal enterotoxin B, ricin, cholera toxin, Bacillus anthracis Sterne, Bacillus globigii, Francisella tularensis LVS, Yersiniapestis F1 antigen, MS2 coliphage, and Salmonella typhimurium. This work maximizes the efficiency and utility of the described array technology, increasing only reagent usage and cost; production and fabrication costs are not affected.

Multiagent intelligent systems

NASA Astrophysics Data System (ADS)

Krause, Lee S.; Dean, Christopher; Lehman, Lynn A.

2003-09-01

This paper will discuss a simulation approach based upon a family of agent-based models. As the demands placed upon simulation technology by such applications as Effects Based Operations (EBO), evaluations of indicators and warnings surrounding homeland defense and commercial demands such financial risk management current single thread based simulations will continue to show serious deficiencies. The types of "what if" analysis required to support these types of applications, demand rapidly re-configurable approaches capable of aggregating large models incorporating multiple viewpoints. The use of agent technology promises to provide a broad spectrum of models incorporating differing viewpoints through a synthesis of a collection of models. Each model would provide estimates to the overall scenario based upon their particular measure or aspect. An agent framework, denoted as the "family" would provide a common ontology in support of differing aspects of the scenario. This approach permits the future of modeling to change from viewing the problem as a single thread simulation, to take into account multiple viewpoints from different models. Even as models are updated or replaced the agent approach permits rapid inclusion in new or modified simulations. In this approach a variety of low and high-resolution information and its synthesis requires a family of models. Each agent "publishes" its support for a given measure and each model provides their own estimates on the scenario based upon their particular measure or aspect. If more than one agent provides the same measure (e.g. cognitive) then the results from these agents are combined to form an aggregate measure response. The objective would be to inform and help calibrate a qualitative model, rather than merely to present highly aggregated statistical information. As each result is processed, the next action can then be determined. This is done by a top-level decision system that communicates to the family at the ontology level without any specific understanding of the processes (or model) behind each agent. The increasingly complex demands upon simulation for the necessity to incorporate the breadth and depth of influencing factors makes a family of agent based models a promising solution. This paper will discuss that solution with syntax and semantics necessary to support the approach.

Which is more effective for suppressing an infectious disease: imperfect vaccination or defense against contagion?

NASA Astrophysics Data System (ADS)

Kuga, Kazuki; Tanimoto, Jun

2018-02-01

We consider two imperfect ways to protect against an infectious disease such as influenza, namely vaccination giving only partial immunity and a defense against contagion such as wearing a mask. We build up a new analytic framework considering those two cases instead of perfect vaccination, conventionally assumed as a premise, with the assumption of an infinite and well-mixed population. Our framework also considers three different strategy-updating rules based on evolutionary game theory: conventional pairwise comparison with one randomly selected agent, another concept of pairwise comparison referring to a social average, and direct alternative selection not depending on the usual copying concept. We successfully obtain a phase diagram in which vaccination coverage at equilibrium can be compared when assuming the model of either imperfect vaccination or a defense against contagion. The obtained phase diagram reveals that a defense against contagion is marginally inferior to an imperfect vaccination as long as the same coefficient value is used. Highlights - We build a new analytical framework for a vaccination game combined with the susceptible-infected-recovered (SIR) model. - Our model can evaluate imperfect provisions such as vaccination giving only partial immunity and a defense against contagion. - We obtain a phase diagram with which to compare the quantitative effects of partial vaccination and a defense against contagion.

Generalized analytical solutions to multispecies transport equations with scale-dependent dispersion coefficients subject to time-dependent boundary conditions

NASA Astrophysics Data System (ADS)

Chen, J. S.; Chiang, S. Y.; Liang, C. P.

2017-12-01

It is essential to develop multispecies transport analytical models based on a set of advection-dispersion equations (ADEs) coupled with sequential first-order decay reactions for the synchronous prediction of plume migrations of both parent and its daughter species of decaying contaminants such as radionuclides, dissolved chlorinated organic compounds, pesticides and nitrogen. Although several analytical models for multispecies transport have already been reported, those currently available in the literature have primarily been derived based on ADEs with constant dispersion coefficients. However, there have been a number of studies demonstrating that the dispersion coefficients increase with the solute travel distance as a consequence of variation in the hydraulic properties of the porous media. This study presents novel analytical models for multispecies transport with distance-dependent dispersion coefficients. The correctness of the derived analytical models is confirmed by comparing them against the numerical models. Results show perfect agreement between the analytical and numerical models. Comparison of our new analytical model for multispecies transport with scale-dependent dispersion to an analytical model with constant dispersion is made to illustrate the effects of the dispersion coefficients on the multispecies transport of decaying contaminants.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †

PubMed Central

Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

2017-01-01

Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. PMID:28208697

Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control.

PubMed

Reinhart, René Felix; Shareef, Zeeshan; Steil, Jochen Jakob

2017-02-08

Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms.

Development and verification of an agent-based model of opinion leadership.

PubMed

Anderson, Christine A; Titler, Marita G

2014-09-27

The use of opinion leaders is a strategy used to speed the process of translating research into practice. Much is still unknown about opinion leader attributes and activities and the context in which they are most effective. Agent-based modeling is a methodological tool that enables demonstration of the interactive and dynamic effects of individuals and their behaviors on other individuals in the environment. The purpose of this study was to develop and test an agent-based model of opinion leadership. The details of the design and verification of the model are presented. The agent-based model was developed by using a software development platform to translate an underlying conceptual model of opinion leadership into a computer model. Individual agent attributes (for example, motives and credibility) and behaviors (seeking or providing an opinion) were specified as variables in the model in the context of a fictitious patient care unit. The verification process was designed to test whether or not the agent-based model was capable of reproducing the conditions of the preliminary conceptual model. The verification methods included iterative programmatic testing ('debugging') and exploratory analysis of simulated data obtained from execution of the model. The simulation tests included a parameter sweep, in which the model input variables were adjusted systematically followed by an individual time series experiment. Statistical analysis of model output for the 288 possible simulation scenarios in the parameter sweep revealed that the agent-based model was performing, consistent with the posited relationships in the underlying model. Nurse opinion leaders act on the strength of their beliefs and as a result, become an opinion resource for their uncertain colleagues, depending on their perceived credibility. Over time, some nurses consistently act as this type of resource and have the potential to emerge as opinion leaders in a context where uncertainty exists. The development and testing of agent-based models is an iterative process. The opinion leader model presented here provides a basic structure for continued model development, ongoing verification, and the establishment of validation procedures, including empirical data collection.

S-2 stage 1/25 scale model base region thermal environment test. Volume 1: Test results, comparison with theory and flight data

NASA Technical Reports Server (NTRS)

Sadunas, J. A.; French, E. P.; Sexton, H.

1973-01-01

A 1/25 scale model S-2 stage base region thermal environment test is presented. Analytical results are included which reflect the effect of engine operating conditions, model scale, turbo-pump exhaust gas injection on base region thermal environment. Comparisons are made between full scale flight data, model test data, and analytical results. The report is prepared in two volumes. The description of analytical predictions and comparisons with flight data are presented. Tabulation of the test data is provided.

Kinetics of wealth and the Pareto law

NASA Astrophysics Data System (ADS)

Boghosian, Bruce M.

2014-04-01

An important class of economic models involve agents whose wealth changes due to transactions with other agents. Several authors have pointed out an analogy with kinetic theory, which describes molecules whose momentum and energy change due to interactions with other molecules. We pursue this analogy and derive a Boltzmann equation for the time evolution of the wealth distribution of a population of agents for the so-called Yard-Sale Model of wealth exchange. We examine the solutions to this equation by a combination of analytical and numerical methods and investigate its long-time limit. We study an important limit of this equation for small transaction sizes and derive a partial integrodifferential equation governing the evolution of the wealth distribution in a closed economy. We then describe how this model can be extended to include features such as inflation, production, and taxation. In particular, we show that the model with taxation exhibits the basic features of the Pareto law, namely, a lower cutoff to the wealth density at small values of wealth, and approximate power-law behavior at large values of wealth.

Opinion dynamics on an adaptive random network

NASA Astrophysics Data System (ADS)

Benczik, I. J.; Benczik, S. Z.; Schmittmann, B.; Zia, R. K. P.

2009-04-01

We revisit the classical model for voter dynamics in a two-party system with two basic modifications. In contrast to the original voter model studied in regular lattices, we implement the opinion formation process in a random network of agents in which interactions are no longer restricted by geographical distance. In addition, we incorporate the rapidly changing nature of the interpersonal relations in the model. At each time step, agents can update their relationships. This update is determined by their own opinion, and by their preference to make connections with individuals sharing the same opinion, or rather with opponents. In this way, the network is built in an adaptive manner, in the sense that its structure is correlated and evolves with the dynamics of the agents. The simplicity of the model allows us to examine several issues analytically. We establish criteria to determine whether consensus or polarization will be the outcome of the dynamics and on what time scales these states will be reached. In finite systems consensus is typical, while in infinite systems a disordered metastable state can emerge and persist for infinitely long time before consensus is reached.

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

Development of a selective and sensitive flotation method for determination of trace amounts of cobalt, nickel, copper and iron in environmental samples.

PubMed

Karimi, H; Ghaedi, M; Shokrollahi, A; Rajabi, H R; Soylak, M; Karami, B

2008-02-28

A simple, selective and rapid flotation method for the separation-preconcentration of trace amounts of cobalt, nickel, iron and copper ions using phenyl 2-pyridyl ketone oxime (PPKO) has been developed prior to their flame atomic absorption spectrometric determinations. The influence of pH, amount of PPKO as collector, type and amount of eluting agent, type and amount of surfactant as floating agent and ionic strength was evaluated on the recoveries of analytes. The influences of the concomitant ions on the recoveries of the analyte ions were also examined. The enrichment factor was 93. The detection limits based on 3 sigma for Cu, Ni, Co and Fe were 0.7, 0.7, 0.8, and 0.7 ng mL(-1), respectively. The method has been successfully applied for determination of trace amounts of ions in various real samples.

Portable Solid Phase Micro-Extraction Coupled with Ion Mobility Spectrometry System for On-Site Analysis of Chemical Warfare Agents and Simulants in Water Samples

PubMed Central

Yang, Liu; Han, Qiang; Cao, Shuya; Yang, Jie; Yang, Junchao; Ding, Mingyu

2014-01-01

On-site analysis is an efficient approach to facilitate analysis at the location of the system under investigation as it can result in more accurate, more precise and quickly available analytical data. In our work, a novel self-made thermal desorption based interface was fabricated to couple solid-phase microextraction with ion mobility spectrometry for on-site water analysis. The portable interface can be connected with the front-end of an ion mobility spectrometer directly without other modifications. The analytical performance was evaluated via the extraction of chemical warfare agents and simulants in water samples. Several parameters including ionic strength and extraction time have been investigated in detail. The application of the developed method afforded satisfactory recoveries ranging from 72.9% to 114.4% when applied to the analysis of real water samples. PMID:25384006

Note: Model identification and analysis of bivalent analyte surface plasmon resonance data.

PubMed

Tiwari, Purushottam Babu; Üren, Aykut; He, Jin; Darici, Yesim; Wang, Xuewen

2015-10-01

Surface plasmon resonance (SPR) is a widely used, affinity based, label-free biophysical technique to investigate biomolecular interactions. The extraction of rate constants requires accurate identification of the particular binding model. The bivalent analyte model involves coupled non-linear differential equations. No clear procedure to identify the bivalent analyte mechanism has been established. In this report, we propose a unique signature for the bivalent analyte model. This signature can be used to distinguish the bivalent analyte model from other biphasic models. The proposed method is demonstrated using experimentally measured SPR sensorgrams.

Situation awareness-based agent transparency for human-autonomy teaming effectiveness

NASA Astrophysics Data System (ADS)

Chen, Jessie Y. C.; Barnes, Michael J.; Wright, Julia L.; Stowers, Kimberly; Lakhmani, Shan G.

2017-05-01

We developed the Situation awareness-based Agent Transparency (SAT) model to support human operators' situation awareness of the mission environment through teaming with intelligent agents. The model includes the agent's current actions and plans (Level 1), its reasoning process (Level 2), and its projection of future outcomes (Level 3). Human-inthe-loop simulation experiments have been conducted (Autonomous Squad Member and IMPACT) to illustrate the utility of the model for human-autonomy team interface designs. Across studies, the results consistently showed that human operators' task performance improved as the agents became more transparent. They also perceived transparent agents as more trustworthy.

Explicit equilibria in a kinetic model of gambling

NASA Astrophysics Data System (ADS)

Bassetti, F.; Toscani, G.

2010-06-01

We introduce and discuss a nonlinear kinetic equation of Boltzmann type which describes the evolution of wealth in a pure gambling process, where the entire sum of wealths of two agents is up for gambling, and randomly shared between the agents. For this equation the analytical form of the steady states is found for various realizations of the random fraction of the sum which is shared to the agents. Among others, the exponential distribution appears as steady state in case of a uniformly distributed random fraction, while Gamma distribution appears for a random fraction which is Beta distributed. The case in which the gambling game is only conservative-in-the-mean is shown to lead to an explicit heavy tailed distribution.

Artificial intelligence based decision support for trumpeter swan management

USGS Publications Warehouse

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Agent-based modeling as a tool for program design and evaluation.

PubMed

Lawlor, Jennifer A; McGirr, Sara

2017-12-01

Recently, systems thinking and systems science approaches have gained popularity in the field of evaluation; however, there has been relatively little exploration of how evaluators could use quantitative tools to assist in the implementation of systems approaches therein. The purpose of this paper is to explore potential uses of one such quantitative tool, agent-based modeling, in evaluation practice. To this end, we define agent-based modeling and offer potential uses for it in typical evaluation activities, including: engaging stakeholders, selecting an intervention, modeling program theory, setting performance targets, and interpreting evaluation results. We provide demonstrative examples from published agent-based modeling efforts both inside and outside the field of evaluation for each of the evaluative activities discussed. We further describe potential pitfalls of this tool and offer cautions for evaluators who may chose to implement it in their practice. Finally, the article concludes with a discussion of the future of agent-based modeling in evaluation practice and a call for more formal exploration of this tool as well as other approaches to simulation modeling in the field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Two-population dynamics in a growing network model

NASA Astrophysics Data System (ADS)

Ivanova, Kristinka; Iordanov, Ivan

2012-02-01

We introduce a growing network evolution model with nodal attributes. The model describes the interactions between potentially violent V and non-violent N agents who have different affinities in establishing connections within their own population versus between the populations. The model is able to generate all stable triads observed in real social systems. In the framework of rate equations theory, we employ the mean-field approximation to derive analytical expressions of the degree distribution and the local clustering coefficient for each type of nodes. Analytical derivations agree well with numerical simulation results. The assortativity of the potentially violent network qualitatively resembles the connectivity pattern in terrorist networks that was recently reported. The assortativity of the network driven by aggression shows clearly different behavior than the assortativity of the networks with connections of non-aggressive nature in agreement with recent empirical results of an online social system.

Agent Based Modeling of Collaboration and Work Practices Onboard the International Space Station

NASA Technical Reports Server (NTRS)

Acquisti, Alessandro; Sierhuis, Maarten; Clancey, William J.; Bradshaw, Jeffrey M.; Shaffo, Mike (Technical Monitor)

2002-01-01

The International Space Station is one the most complex projects ever, with numerous interdependent constraints affecting productivity and crew safety. This requires planning years before crew expeditions, and the use of sophisticated scheduling tools. Human work practices, however, are difficult to study and represent within traditional planning tools. We present an agent-based model and simulation of the activities and work practices of astronauts onboard the ISS based on an agent-oriented approach. The model represents 'a day in the life' of the ISS crew and is developed in Brahms, an agent-oriented, activity-based language used to model knowledge in situated action and learning in human activities.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

2011-11-01

There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

Separation of very hydrophobic analytes by micellar electrokinetic chromatography IV. Modeling of the effective electrophoretic mobility from carbon number equivalents and octanol-water partition coefficients.

PubMed

Huhn, Carolin; Pyell, Ute

2008-07-11

It is investigated whether those relationships derived within an optimization scheme developed previously to optimize separations in micellar electrokinetic chromatography can be used to model effective electrophoretic mobilities of analytes strongly differing in their properties (polarity and type of interaction with the pseudostationary phase). The modeling is based on two parameter sets: (i) carbon number equivalents or octanol-water partition coefficients as analyte descriptors and (ii) four coefficients describing properties of the separation electrolyte (based on retention data for a homologous series of alkyl phenyl ketones used as reference analytes). The applicability of the proposed model is validated comparing experimental and calculated effective electrophoretic mobilities. The results demonstrate that the model can effectively be used to predict effective electrophoretic mobilities of neutral analytes from the determined carbon number equivalents or from octanol-water partition coefficients provided that the solvation parameters of the analytes of interest are similar to those of the reference analytes.

Agent-Based Model Approach to Complex Phenomena in Real Economy

NASA Astrophysics Data System (ADS)

Iyetomi, H.; Aoyama, H.; Fujiwara, Y.; Ikeda, Y.; Souma, W.

An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents are described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the ``profit maximization" principle is suppressed by a concept of ``going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

NASA Astrophysics Data System (ADS)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

Modeling the Internet of Things, Self-Organizing and Other Complex Adaptive Communication Networks: A Cognitive Agent-Based Computing Approach

PubMed Central

2016-01-01

Background Computer Networks have a tendency to grow at an unprecedented scale. Modern networks involve not only computers but also a wide variety of other interconnected devices ranging from mobile phones to other household items fitted with sensors. This vision of the "Internet of Things" (IoT) implies an inherent difficulty in modeling problems. Purpose It is practically impossible to implement and test all scenarios for large-scale and complex adaptive communication networks as part of Complex Adaptive Communication Networks and Environments (CACOONS). The goal of this study is to explore the use of Agent-based Modeling as part of the Cognitive Agent-based Computing (CABC) framework to model a Complex communication network problem. Method We use Exploratory Agent-based Modeling (EABM), as part of the CABC framework, to develop an autonomous multi-agent architecture for managing carbon footprint in a corporate network. To evaluate the application of complexity in practical scenarios, we have also introduced a company-defined computer usage policy. Results The conducted experiments demonstrated two important results: Primarily CABC-based modeling approach such as using Agent-based Modeling can be an effective approach to modeling complex problems in the domain of IoT. Secondly, the specific problem of managing the Carbon footprint can be solved using a multiagent system approach. PMID:26812235

Simple and Sensitive Paper-Based Device Coupling Electrochemical Sample Pretreatment and Colorimetric Detection.

PubMed

Silva, Thalita G; de Araujo, William R; Muñoz, Rodrigo A A; Richter, Eduardo M; Santana, Mário H P; Coltro, Wendell K T; Paixão, Thiago R L C

2016-05-17

We report the development of a simple, portable, low-cost, high-throughput visual colorimetric paper-based analytical device for the detection of procaine in seized cocaine samples. The interference of most common cutting agents found in cocaine samples was verified, and a novel electrochemical approach was used for sample pretreatment in order to increase the selectivity. Under the optimized experimental conditions, a linear analytical curve was obtained for procaine concentrations ranging from 5 to 60 μmol L(-1), with a detection limit of 0.9 μmol L(-1). The accuracy of the proposed method was evaluated using seized cocaine samples and an addition and recovery protocol.

A physical data model for fields and agents

NASA Astrophysics Data System (ADS)

de Jong, Kor; de Bakker, Merijn; Karssenberg, Derek

2016-04-01

Two approaches exist in simulation modeling: agent-based and field-based modeling. In agent-based (or individual-based) simulation modeling, the entities representing the system's state are represented by objects, which are bounded in space and time. Individual objects, like an animal, a house, or a more abstract entity like a country's economy, have properties representing their state. In an agent-based model this state is manipulated. In field-based modeling, the entities representing the system's state are represented by fields. Fields capture the state of a continuous property within a spatial extent, examples of which are elevation, atmospheric pressure, and water flow velocity. With respect to the technology used to create these models, the domains of agent-based and field-based modeling have often been separate worlds. In environmental modeling, widely used logical data models include feature data models for point, line and polygon objects, and the raster data model for fields. Simulation models are often either agent-based or field-based, even though the modeled system might contain both entities that are better represented by individuals and entities that are better represented by fields. We think that the reason for this dichotomy in kinds of models might be that the traditional object and field data models underlying those models are relatively low level. We have developed a higher level conceptual data model for representing both non-spatial and spatial objects, and spatial fields (De Bakker et al. 2016). Based on this conceptual data model we designed a logical and physical data model for representing many kinds of data, including the kinds used in earth system modeling (e.g. hydrological and ecological models). The goal of this work is to be able to create high level code and tools for the creation of models in which entities are representable by both objects and fields. Our conceptual data model is capable of representing the traditional feature data models and the raster data model, among many other data models. Our physical data model is capable of storing a first set of kinds of data, like omnipresent scalars, mobile spatio-temporal points and property values, and spatio-temporal rasters. With our poster we will provide an overview of the physical data model expressed in HDF5 and show examples of how it can be used to capture both object- and field-based information. References De Bakker, M, K. de Jong, D. Karssenberg. 2016. A conceptual data model and language for fields and agents. European Geosciences Union, EGU General Assembly, 2016, Vienna.

A model of the demand for Islamic banks debt-based financing instrument

NASA Astrophysics Data System (ADS)

Jusoh, Mansor; Khalid, Norlin

2013-04-01

This paper presents a theoretical analysis of the demand for debt-based financing instruments of the Islamic banks. Debt-based financing, such as through baibithamanajil and al-murabahah, is by far the most prominent of the Islamic bank financing and yet it has been largely ignored in Islamic economics literature. Most studies instead have been focusing on equity-based financing of al-mudharabah and al-musyarakah. Islamic bank offers debt-based financing through various instruments derived under the principle of exchange (ukud al-mu'awadhat) or more specifically, the contract of deferred sale. Under such arrangement, Islamic debt is created when goods are purchased and the payments are deferred. Thus, unlike debt of the conventional bank which is a form of financial loan contract to facilitate demand for liquid assets, this Islamic debt is created in response to the demand to purchase goods by deferred payment. In this paper we set an analytical framework that is based on an infinitely lived representative agent model (ILRA model) to analyze the demand for goods to be purchased by deferred payment. The resulting demand will then be used to derive the demand for Islamic debt. We also investigate theoretically, factors that may have an impact on the demand for Islamic debt.

Diversity-induced resonance in the response to social norms

NASA Astrophysics Data System (ADS)

Tessone, Claudio J.; Sánchez, Angel; Schweitzer, Frank

2013-02-01

In this paper we focus on diversity-induced resonance, which was recently found in bistable, excitable, and other physical systems. We study the appearance of this phenomenon in a purely economic model of cooperating and defecting agents. An agent's contribution to a public good is seen as a social norm, so defecting agents face a social pressure, which decreases if free riding becomes widespread. In this model, diversity among agents naturally appears because of the different sensitivities towards the social norm. We study the evolution of cooperation as a response to the social norm (i) for the replicator dynamics and (ii) for the logit dynamics by means of numerical simulations. Diversity-induced resonance is observed as a maximum in the response of agents to changes in the social norm as a function of the degree of heterogeneity in the population. We provide an analytical, mean-field approach for the logit dynamics and find very good agreement with the simulations. From a socioeconomic perspective, our results show that, counterintuitively, diversity in the individual sensitivity to social norms may result in a society that better follows such norms as a whole, even if part of the population is less prone to follow them.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Model reduction for agent-based social simulation: coarse-graining a civil violence model.

PubMed

Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Model reduction for agent-based social simulation: Coarse-graining a civil violence model

NASA Astrophysics Data System (ADS)

Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

2012-06-01

Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

Sustainability is possible despite greed - Exploring the nexus between profitability and sustainability in common pool resource systems.

PubMed

Osten, Friedrich Burkhard von der; Kirley, Michael; Miller, Tim

2017-05-23

The sustainable use of common pool resources has become a significant global challenge. It is now widely accepted that specific mechanisms such as community-based management strategies, institutional responses such as resource privatization, information availability and emergent social norms can be used to constrain individual 'harvesting' to socially optimal levels. However, there is a paucity of research focused specifically on aligning profitability and sustainability goals. In this paper, an integrated mathematical model of a common pool resource game is developed to explore the nexus between the underlying costs and benefits of harvesting decisions and the sustainable level of a shared, dynamic resource. We derive optimal harvesting efforts analytically and then use numerical simulations to show that individuals in a group can learn to make harvesting decisions that lead to the globally optimal levels. Individual agents make their decision based on signals received and a trade-off between economic and ecological sustainability. When the balance is weighted towards profitability, acceptable economic and social outcomes emerge. However, if individual agents are solely driven by profit, the shared resource is depleted in the long run - sustainability is possible despite some greed, but too much will lead to over-exploitation.

A hybrid model for opinion formation

NASA Astrophysics Data System (ADS)

Borra, Domenica; Lorenzi, Tommaso

2013-06-01

This paper presents a hybrid model for opinion formation in a large group of agents exposed to the persuasive action of a small number of strong opinion leaders. The model is defined by coupling a finite difference equation for the dynamics of leaders opinion with a continuous integro-differential equation for the dynamics of the others. Such a definition stems from the idea that the leaders are few and tend to retain original opinions, so that their dynamics occur on a longer time scale with respect to the one of the other agents. A general well-posedness result is established for the initial value problem linked to the model. The asymptotic behavior in time of the related solution is characterized for some general parameter settings, which mimic distinct social scenarios, where different emerging behaviors can be observed. Analytical results are illustrated and extended through numerical simulations.

Persuasion Model and Its Evaluation Based on Positive Change Degree of Agent Emotion

NASA Astrophysics Data System (ADS)

Jinghua, Wu; Wenguang, Lu; Hailiang, Meng

For it can meet needs of negotiation among organizations take place in different time and place, and for it can make its course more rationality and result more ideal, persuasion based on agent can improve cooperation among organizations well. Integrated emotion change in agent persuasion can further bring agent advantage of artificial intelligence into play. Emotion of agent persuasion is classified, and the concept of positive change degree is given. Based on this, persuasion model based on positive change degree of agent emotion is constructed, which is explained clearly through an example. Finally, the method of relative evaluation is given, which is also verified through a calculation example.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

NASA Astrophysics Data System (ADS)

Braga, Jez Willian Batista; Trevizan, Lilian Cristina; Nunes, Lidiane Cristina; Rufini, Iolanda Aparecida; Santos, Dário, Jr.; Krug, Francisco José

2010-01-01

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance, but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Let's Go Off the Grid: Subsurface Flow Modeling With Analytic Elements

NASA Astrophysics Data System (ADS)

Bakker, M.

2017-12-01

Subsurface flow modeling with analytic elements has the major advantage that no grid or time stepping are needed. Analytic element formulations exist for steady state and transient flow in layered aquifers and unsaturated flow in the vadose zone. Analytic element models are vector-based and consist of points, lines and curves that represent specific features in the subsurface. Recent advances allow for the simulation of partially penetrating wells and multi-aquifer wells, including skin effect and wellbore storage, horizontal wells of poly-line shape including skin effect, sharp changes in subsurface properties, and surface water features with leaky beds. Input files for analytic element models are simple, short and readable, and can easily be generated from, for example, GIS databases. Future plans include the incorporation of analytic element in parts of grid-based models where additional detail is needed. This presentation will give an overview of advanced flow features that can be modeled, many of which are implemented in free and open-source software.

New-generation bar adsorptive microextraction (BAμE) devices for a better eco-user-friendly analytical approach-Application for the determination of antidepressant pharmaceuticals in biological fluids.

PubMed

Ide, A H; Nogueira, J M F

2018-05-10

The present contribution aims to design new-generation bar adsorptive microextraction (BAμE) devices that promote an innovative and much better user-friendly analytical approach. The novel BAμE devices were lab-made prepared having smaller dimensions by using flexible nylon-based supports (7.5 × 1.0 mm) coated with convenient sorbents (≈ 0.5 mg). This novel advance allows effective microextraction and back-extraction ('only single liquid desorption step') stages as well as interfacing enhancement with the instrumental systems dedicated for routine analysis. To evaluate the achievements of these improvements, four antidepressant agents (bupropion, citalopram, amitriptyline and trazodone) were used as model compounds in aqueous media combined with liquid chromatography (LC) systems. By using an N-vinylpyrrolidone based-polymer phase good selectivity and efficiency were obtained. Assays performed on 25 mL spiked aqueous samples, yielded average recoveries in between 67.8 ± 12.4% (bupropion) and 88.3 ± 12.1% (citalopram), under optimized experimental conditions. The analytical performance also showed convenient precision (RSD < 12%) and detection limits (50 ng L -1 ), as well as linear dynamic ranges (160-2000 ng L -1 ) with suitable determination coefficients (r 2  > 0.9820). The application of the proposed analytical approach on biological fluids showed negligible matrix effects by using the standard addition methodology. From the data obtained, the new-generation BAμE devices presented herein provide an innovative and robust analytical cycle, are simple to prepare, cost-effective, user-friendly and compatible with the current LC autosampler systems. Furthermore, the novel devices were designed to be disposable and used together with negligible amounts of organic solvents (100 μL) during back-extraction, in compliance with the green analytical chemistry principles. In short, the new-generation BAμE devices showed to be an eco-user-friendly approach for trace analysis of priority compounds in biological fluids and a versatile alternative over other well-stablished sorption-based microextraction techniques. Copyright © 2018 Elsevier B.V. All rights reserved.

Improving a complex finite-difference ground water flow model through the use of an analytic element screening model

USGS Publications Warehouse

Hunt, R.J.; Anderson, M.P.; Kelson, V.A.

1998-01-01

This paper demonstrates that analytic element models have potential as powerful screening tools that can facilitate or improve calibration of more complicated finite-difference and finite-element models. We demonstrate how a two-dimensional analytic element model was used to identify errors in a complex three-dimensional finite-difference model caused by incorrect specification of boundary conditions. An improved finite-difference model was developed using boundary conditions developed from a far-field analytic element model. Calibration of a revised finite-difference model was achieved using fewer zones of hydraulic conductivity and lake bed conductance than the original finite-difference model. Calibration statistics were also improved in that simulated base-flows were much closer to measured values. The improved calibration is due mainly to improved specification of the boundary conditions made possible by first solving the far-field problem with an analytic element model.This paper demonstrates that analytic element models have potential as powerful screening tools that can facilitate or improve calibration of more complicated finite-difference and finite-element models. We demonstrate how a two-dimensional analytic element model was used to identify errors in a complex three-dimensional finite-difference model caused by incorrect specification of boundary conditions. An improved finite-difference model was developed using boundary conditions developed from a far-field analytic element model. Calibration of a revised finite-difference model was achieved using fewer zones of hydraulic conductivity and lake bed conductance than the original finite-difference model. Calibration statistics were also improved in that simulated base-flows were much closer to measured values. The improved calibration is due mainly to improved specification of the boundary conditions made possible by first solving the far-field problem with an analytic element model.

An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

NASA Astrophysics Data System (ADS)

Hu, Xiaolin; Puddy, Richard W.

This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Final Report: PAGE: Policy Analytics Generation Engine

DTIC Science & Technology

2016-08-12

develop a parallel framework for it. We also developed policies and methods by which a group of defensive resources (e.g. checkpoints) could be...Sarit Kraus. Learning to Reveal Information in Repeated Human -Computer Negotiation, Human -Agent Interaction Design and Models Workshop 2012. 04-JUN...Joseph Keshet, Sarit Kraus. Predicting Human Strategic Decisions Using Facial Expressions, International Joint Conference on Artificial

The use of analytical models in human-computer interface design

NASA Technical Reports Server (NTRS)

Gugerty, Leo

1991-01-01

Some of the many analytical models in human-computer interface design that are currently being developed are described. The usefulness of analytical models for human-computer interface design is evaluated. Can the use of analytical models be recommended to interface designers? The answer, based on the empirical research summarized here, is: not at this time. There are too many unanswered questions concerning the validity of models and their ability to meet the practical needs of design organizations.

Effects of encapsulation damping on the excitation threshold for subharmonic generation from contrast microbubbles.

PubMed

Katiyar, Amit; Sarkar, Kausik

2012-11-01

A recent study [Katiyar and Sarkar (2011). J. Acoust. Soc. Am. 130, 3137-3147] showed that in contrast to the analytical result for free bubbles, the minimum threshold for subharmonic generation for contrast microbubbles does not necessarily occur at twice the resonance frequency. Here increased damping-either due to the small radius or the encapsulation-is shown to shift the minimum threshold away from twice the resonance frequency. Free bubbles as well as four models of the contrast agent encapsulation are investigated varying the surface dilatational viscosity. Encapsulation properties are determined using measured attenuation data for a commercial contrast agent. For sufficiently small damping, models predict two minima for the threshold curve-one at twice the resonance frequency being lower than the other at resonance frequency-in accord with the classical analytical result. However, increased damping damps the bubble response more at twice the resonance than at resonance, leading to a flattening of the threshold curve and a gradual shift of the absolute minimum from twice the resonance frequency toward the resonance frequency. The deviation from the classical result stems from the fact that the perturbation analysis employed to obtain it assumes small damping, not always applicable for contrast microbubbles.

Devices and methods to detect and quantify trace gases

DOEpatents

Allendorf, Mark D.; Robinson, Alex

2016-05-03

Sensing devices based on a surface acoustic wave ("SAW") device coated with an absorbent crystalline or amorphous layer for detecting at least one chemical analyte in a gaseous carrier. Methods for detecting the presence of a chemical analyte in a gaseous carrier using such devices are also disclosed. The sensing devices and methods for their use may be configured for sensing chemical analytes selected from the group consisting of water vapor, carbon dioxide, methanol, ethanol, carbon monoxide, nitric oxide, nitrous oxide, organic amines, organic compounds containing NO.sub.2 groups, halogenated hydrocarbons, acetone, hexane, toluene, isopropanol, alcohols, alkanes, alkenes, benzene, functionalized aromatics, ammonia (NH.sub.3), phosgene (COCl.sub.2), sulfur mustard, nerve agents, sulfur dioxide, tetrahydrofuran (THF) and methyltertbutyl ether (MTBE) and combinations thereof.

Patterns of cooperation: fairness and coordination in networks of interacting agents

NASA Astrophysics Data System (ADS)

Do, Anne-Ly; Rudolf, Lars; Gross, Thilo

2010-06-01

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively and independently adapt the amount of resources allocated to each of their collaborations in order to maximize the obtained payoff. We show analytically that the system approaches a state in which the agents make identical investments, and links produce identical benefits. Despite this high degree of social coordination, some agents manage to secure privileged topological positions in the network, enabling them to extract high payoffs. Our analytical investigations provide a rationale for the emergence of unidirectional non-reciprocal collaborations and different responses to the withdrawal of a partner from an interaction that have been reported in the psychological literature.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

B-tree search reinforcement learning for model based intelligent agent

NASA Astrophysics Data System (ADS)

Bhuvaneswari, S.; Vignashwaran, R.

2013-03-01

Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course.

Noise and the statistical mechanics of distributed transport in a colony of interacting agents

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Graewer, Johannes; Ronellenfitsch, Henrik; Mazza, Marco G.

Inspired by the process of liquid food distribution between individuals in an ant colony, in this work we consider the statistical mechanics of resource dissemination between interacting agents with finite carrying capacity. The agents move inside a confined space (nest), pick up the food at the entrance of the nest and share it with other agents that they encounter. We calculate analytically and via a series of simulations the global food intake rate for the whole colony as well as observables describing how uniformly the food is distributed within the nest. Our model and predictions provide a useful benchmark to assess which strategies can lead to efficient food distribution within the nest and also to what level the observed food uptake rates and efficiency in food distribution are due to stochastic fluctuations or specific food exchange strategies by an actual ant colony.

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

NASA Technical Reports Server (NTRS)

Campbell, Kenyth

2012-01-01

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

Review of the systems biology of the immune system using agent-based models.

PubMed

Shinde, Snehal B; Kurhekar, Manish P

2018-06-01

The immune system is an inherent protection system in vertebrate animals including human beings that exhibit properties such as self-organisation, self-adaptation, learning, and recognition. It interacts with the other allied systems such as the gut and lymph nodes. There is a need for immune system modelling to know about its complex internal mechanism, to understand how it maintains the homoeostasis, and how it interacts with the other systems. There are two types of modelling techniques used for the simulation of features of the immune system: equation-based modelling (EBM) and agent-based modelling. Owing to certain shortcomings of the EBM, agent-based modelling techniques are being widely used. This technique provides various predictions for disease causes and treatments; it also helps in hypothesis verification. This study presents a review of agent-based modelling of the immune system and its interactions with the gut and lymph nodes. The authors also review the modelling of immune system interactions during tuberculosis and cancer. In addition, they also outline the future research directions for the immune system simulation through agent-based techniques such as the effects of stress on the immune system, evolution of the immune system, and identification of the parameters for a healthy immune system.

Ionic liquid as a mobile phase additive in high-performance liquid chromatography for the simultaneous determination of eleven fluorescent whitening agents in paper materials.

PubMed

Wang, Qing; Chen, Xianbo; Qiu, Bin; Zhou, Liang; Zhang, Hui; Xie, Juan; Luo, Yan; Wang, Bin

2016-04-01

In the present study, 11 4,4'-diaminostilbene-2,2'-disulfonic acid based fluorescent whitening agents with different numbers of sulfonic acid groups were separated by using an ionic liquid as a mobile phase additive in high-performance liquid chromatography with fluorescence detection. The effects of ionic liquid concentration, pH of mobile phase B, and composition of mobile phase A on the separation of fluorescent whitening agents were systematically investigated. The ionic liquid tetrabutylammonium tetrafluoroborate is superior to tetrabutylammomnium bromide for the separation of the fluorescent whitening agents. The optimal separation conditions were an ionic liquid concentration at 8 mM and the pH of mobile phase B at 8.5 with methanol as mobile phase A. The established method exhibited low limits of detection (0.04-0.07 ng/mL) and wide linearity ranges (0.30-20 ng/mL) with high linear correlation coefficients from 0.9994 to 0.9998. The optimized procedure was applied to analyze target analytes in paper samples with satisfactory results. Eleven target analytes were quantified, and the recoveries of spiked paper samples were in the range of 85-105% with the relative standard deviations from 2.1 to 5.1%. The obtained results indicated that the method was efficient for detection of 11 fluorescent whitening agents. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From continuous to discontinuous transitions in social diffusion

NASA Astrophysics Data System (ADS)

Tuzón, Paula; Fernández-Gracia, Juan; Eguíluz, Víctor M.

2018-03-01

Models of social diffusion reflect processes of how new products, ideas or behaviors are adopted in a population. These models typically lead to a continuous or a discontinuous phase transition of the number of adopters as a function of a control parameter. We explore a simple model of social adoption where the agents can be in two states, either adopters or non-adopters, and can switch between these two states interacting with other agents through a network. The probability of an agent to switch from non-adopter to adopter depends on the number of adopters in her network neighborhood, the adoption threshold T and the adoption coefficient a, two parameters defining a Hill function. In contrast the transition from adopter to non-adopter is spontaneous at a certain rate μ. In a mean-field approach, we derive the governing ordinary differential equations and show that the nature of the transition between the global non-adoption and global adoption regimes depends mostly on the balance between the probability to adopt with one and two adopters. The transition changes from continuous, via a transcritical bifurcation, to discontinuous, via a combination of a saddle-node and a transcritical bifurcation, through a supercritical pitchfork bifurcation. We characterize the full parameter space. Finally, we compare our analytical results with Montecarlo simulations on annealed and quenched degree regular networks, showing a better agreement for the annealed case. Our results show how a simple model is able to capture two seemingly very different types of transitions, i.e., continuous and discontinuous and thus unifies underlying dynamics for different systems. Furthermore the form of the adoption probability used here is based on empirical measurements.

Chronic Heart Failure Follow-up Management Based on Agent Technology.

PubMed

Mohammadzadeh, Niloofar; Safdari, Reza

2015-10-01

Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making.

Application of the Novel 5-chloro-2,2,3,3,4,4,5,5-octafluoro-1-pentyl Chloroformate Derivatizing Agent for the Direct Determination of Highly Polar Water Disinfection Byproducts

EPA Science Inventory

A novel derivatizing agent, 5-chloro-2,2,3,3,4,4,5,5-octafluoropentyl chloroformate (ClOFPCF), was synthesized and tested as a reagent for direct water derivatization of highly polar and hydrophilic analytes. Its analytical performance satisfactorily compared to a perfluorinated ...

The Soil Carbon Paradigm Shift: Triangulating Theories, Measurements, and Models

NASA Astrophysics Data System (ADS)

Blankinship, J. C.; Crow, S. E.; Schimel, J.; Sierra, C. A.; Schaedel, C.; Plante, A. F.; Thompson, A.; Berhe, A. A.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Rasmussen, C.; Wagai, R.; Wieder, W. R.

2016-12-01

Predicting global responses of soil carbon (C) to environmental change remains confounded by a number of paradigms that have emerged from separate approaches. A prevailing paradigm in biogeochemistry interprets soil C as discrete pools based on estimated or measured turnover times (e.g., CENTURY model). An alternative is emerging that envisions the stabilization of soil C in tension between decomposition by microbial agents and protection by physical and chemical mechanisms. We propose an approach to bridge the gap between different paradigms, and to improve soil C forecasting by conceptualizing each paradigm as a triangle composed of three nodes: theory, analytical measurement, and numerical model. Paradigms tend to emerge from what can either be represented in models or measured using analytical instruments. But they gain power when all three elements are integrated in a balanced trinity. Our goal was to compare how theory, measurement, and model fit together in our understanding of soil C to learn from past successes, evaluate the strengths and weaknesses of current paradigms, and guide development of new understanding. We used a case-study approach to analyze each corner of the paradigm-triangle: i) paradigms that have strong theory but are constrained by weak linkages with measurements or models, ii) paradigms with robust models that have weak linkages with theory or measurements, and iii) paradigms with many measurements but little theoretical support or ability to be parameterized in numerical models. We conclude that established models like CENTURY dominate because theory and measurements that underlie the model form strong linkages that previously created a balanced triangle. Evolving paradigms based on physical protection and microbial agency are still struggling to gain traction because the theory is challenging to represent in models. The explicit examination of the strengths of emerging paradigms can, therefore, help refine and accelerate our ability to constrain projections of soil C dynamics.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Scoping Planning Agents With Shared Models

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Frank, Jeremy D.; Jonsson, Ari K.; McGann, Conor

2003-01-01

In this paper we provide a formal framework to define the scope of planning agents based on a single declarative model. Having multiple agents sharing a single model provides numerous advantages that lead to reduced development costs and increase reliability of the system. We formally define planning in terms of extensions of an initial partial plan, and a set of flaws that make the plan unacceptable. A Flaw Filter (FF) allows us to identify those flaws relevant to an agent. Flaw filters motivate the Plan Identification Function (PIF), which specifies when an agent is is ready hand control to another agent for further work. PIFs define a set of plan extensions that can be generated from a model and a plan request. FFs and PIFs can be used to define the scope of agents without changing the model. We describe an implementation of PIFsand FFswithin the context of EUROPA, a constraint-based planning architecture, and show how it can be used to easily design many different agents.

An Agent-Based Data Mining System for Ontology Evolution

NASA Astrophysics Data System (ADS)

Hadzic, Maja; Dillon, Darshan

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

Repeated applications of a transdermal patch: analytical solution and optimal control of the delivery rate.

PubMed

Simon, L

2007-10-01

The integral transform technique was implemented to solve a mathematical model developed for percutaneous drug absorption. The model included repeated application and removal of a patch from the skin. Fick's second law of diffusion was used to study the transport of a medicinal agent through the vehicle and subsequent penetration into the stratum corneum. Eigenmodes and eigenvalues were computed and introduced into an inversion formula to estimate the delivery rate and the amount of drug in the vehicle and the skin. A dynamic programming algorithm calculated the optimal doses necessary to achieve a desired transdermal flux. The analytical method predicted profiles that were in close agreement with published numerical solutions and provided an automated strategy to perform therapeutic drug monitoring and control.

Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

PubMed

Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

2010-06-29

In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes. The good agreement between the two modeling approaches is very important for defining the tradeoff between data availability and the information provided by the models. The results we present define the possibility of hybrid models combining the agent-based and the metapopulation approaches according to the available data and computational resources.

Strategies to Enhance Online Learning Teams. Team Assessment and Diagnostics Instrument and Agent-based Modeling

DTIC Science & Technology

2010-08-12

Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT

Agent-based modeling: Methods and techniques for simulating human systems

PubMed Central

Bonabeau, Eric

2002-01-01

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

Agent based modeling of the coevolution of hostility and pacifism

NASA Astrophysics Data System (ADS)

Dalmagro, Fermin; Jimenez, Juan

2015-01-01

We propose a model based on a population of agents whose states represent either hostile or peaceful behavior. Randomly selected pairs of agents interact according to a variation of the Prisoners Dilemma game, and the probabilities that the agents behave aggressively or not are constantly updated by the model so that the agents that remain in the game are those with the highest fitness. We show that the population of agents oscillate between generalized conflict and global peace, without either reaching a stable state. We then use this model to explain some of the emergent behaviors in collective conflicts, by comparing the simulated results with empirical data obtained from social systems. In particular, using public data reports we show how the model precisely reproduces interesting quantitative characteristics of diverse types of armed conflicts, public protests, riots and strikes.

Considerations in detecting CDC select agents under field conditions

NASA Astrophysics Data System (ADS)

Spinelli, Charles; Soelberg, Scott; Swanson, Nathaneal; Furlong, Clement; Baker, Paul

2008-04-01

Surface Plasmon Resonance (SPR) has become a widely accepted technique for real-time detection of interactions between receptor molecules and ligands. Antibody may serve as receptor and can be attached to the gold surface of the SPR device, while candidate analyte fluids contact the detecting antibody. Minute, but detectable, changes in refractive indices (RI) indicate that analyte has bound to the antibody. A decade ago, an inexpensive, robust, miniature and fully integrated SPR chip, called SPREETA, was developed. University of Washington (UW) researchers subsequently developed a portable, temperature-regulated instrument, called SPIRIT, to simultaneously use eight of these three-channel SPREETA chips. A SPIRIT prototype instrument was tested in the field, coupled to a remote reporting system on a surrogate unmanned aerial vehicle (UAV). Two target protein analytes were released sequentially as aerosols with low analyte concentration during each of three flights and were successfully detected and verified. Laboratory experimentation with a more advanced SPIRIT instrument demonstrated detection of very low levels of several select biological agents that might be employed by bioterrorists. Agent detection under field-like conditions is more challenging, especially as analyte concentrations are reduced and complex matricies are introduced. Two different sample preconditioning protocols have been developed for select agents in complex matrices. Use of these preconditioning techniques has allowed laboratory detection in spiked heavy mud of Francisella tularensis at 10 3 CFU/ml, Bacillus anthracis spores at 10 3 CFU/ml, Staphylococcal enterotoxin B (SEB) at 1 ng/ml, and Vaccinia virus (a smallpox simulant) at 10 5 PFU/ml. Ongoing experiments are aimed at simultaneous detection of multiple agents in spiked heavy mud, using a multiplex preconditioning protocol.

Investigation of the persistence of nerve agent degradation analytes on surfaces through wipe sampling and detection with ultrahigh performance liquid chromatography-tandem mass spectrometry.

PubMed

Willison, Stuart A

2015-01-20

The persistence of chemical warfare nerve agent degradation analytes on surfaces is important, from indicating the presence of nerve agent on a surface to guiding environmental restoration of a site after a release. Persistence was investigated for several chemical warfare nerve agent degradation analytes on indoor surfaces and presents an approach for wipe sampling of surfaces, followed by wipe extraction and liquid chromatography-tandem mass spectrometry detection. Commercially available wipe materials were investigated to determine optimal wipe recoveries. Tested surfaces included porous/permeable (vinyl tile, painted drywall, and wood) and largely nonporous/impermeable (laminate, galvanized steel, and glass) surfaces. Wipe extracts were analyzed by ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). UPLC provides a separation of targeted degradation analytes in addition to being nearly four times faster than high-performance liquid chromatography, allowing for greater throughput after a large-scale contamination incident and subsequent remediation events. Percent recoveries from nonporous/impermeable surfaces were 60-103% for isopropyl methylphosphonate (IMPA), GB degradate; 61-91% for ethyl methylphosphonate (EMPA), VX degradate; and 60-98% for pinacolyl methylphosphonate (PMPA), GD degradate. Recovery efficiencies for methyl phosphonate (MPA), nerve agent degradate, and ethylhydrogen dimethylphosphonate (EHDMAP), GA degradate, were lower, perhaps due to matrix effects. Diisopropyl methylphosphonate, GB impurity, was not recovered from surfaces. The resulting detection limits for wipe extracts were 0.065 ng/cm(2) for IMPA, 0.079 ng/cm(2) for MPA, 0.040 ng/cm(2) for EMPA, 0.078 ng/cm(2) for EHDMAP, and 0.013 ng/cm(2) for PMPA. The data indicate that laboratories may hold wipe samples for up to 30 days prior to analysis. Target analytes were observed to persist on surfaces for at least 6 weeks.

The Freter model: a simple model of biofilm formation.

PubMed

Jones, Don; Kojouharov, Hristo V; Le, Dung; Smith, Hal

2003-08-01

A simple, conceptual model of biofilm formation, due to R. Freter et al. (1983), is studied analytically and numerically in both CSTR and PFR. Two steady state regimes are identified, namely, the complete washout of the microbes from the reactor and the successful colonization of both the wall and bulk fluid. One of these is stable for any particular set of parameter values and sharp and explicit conditions are given for the stability of each. The effects of adding an anti-microbial agent to the CSTR are examined.

Analytic solutions for single and multiple cylinders of gravitating polytropes in magnetostatic equilibrium

NASA Technical Reports Server (NTRS)

Lerche, I.; Low, B. C.

1980-01-01

Exact analytic solutions for the static equilibrium of a gravitating plasma polytrope in the presence of magnetic fields are presented. The means of generating various equilibrium configurations to illustrate directly the complex physical relationships between pressure, magnetic fields, and gravity in self-gravitating systems is demonstrated. One of the solutions is used to model interstellar clouds suspended by magnetic fields against the galactic gravity such as may be formed by the Parker (1966) instability. It is concluded that the pinching effect of closed loops of magnetic fields in the clouds may be a dominant agent in further collapsing the clouds following their formation.

Thermal luminescence spectroscopy chemical imaging sensor.

PubMed

Carrieri, Arthur H; Buican, Tudor N; Roese, Erik S; Sutter, James; Samuels, Alan C

2012-10-01

The authors present a pseudo-active chemical imaging sensor model embodying irradiative transient heating, temperature nonequilibrium thermal luminescence spectroscopy, differential hyperspectral imaging, and artificial neural network technologies integrated together. We elaborate on various optimizations, simulations, and animations of the integrated sensor design and apply it to the terrestrial chemical contamination problem, where the interstitial contaminant compounds of detection interest (analytes) comprise liquid chemical warfare agents, their various derivative condensed phase compounds, and other material of a life-threatening nature. The sensor must measure and process a dynamic pattern of absorptive-emissive middle infrared molecular signature spectra of subject analytes to perform its chemical imaging and standoff detection functions successfully.

An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Sadiig, I. Ahmed M. J.

2005-01-01

The traditional learning paradigm involving face-to-face interaction with students is shifting to highly data-intensive electronic learning with the advances in Information and Communication Technology. An important component of the e-learning process is the delivery of the learning contents to their intended audience over a network. A distributed…

Validation of the replica trick for simple models

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-04-01

We discuss the replica analytic continuation using several simple models in order to prove mathematically the validity of the replica analysis, which is used in a wide range of fields related to large-scale complex systems. While replica analysis consists of two analytical techniques—the replica trick (or replica analytic continuation) and the thermodynamical limit (and/or order parameter expansion)—we focus our study on replica analytic continuation, which is the mathematical basis of the replica trick. We apply replica analysis to solve a variety of analytical models, and examine the properties of replica analytic continuation. Based on the positive results for these models we propose that replica analytic continuation is a robust procedure in replica analysis.

Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

PubMed Central

Marshall, Brandon D. L.; Galea, Sandro

2015-01-01

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. PMID:25480821

Pentafluorobenzyl bromide-A versatile derivatization agent in chromatography and mass spectrometry: I. Analysis of inorganic anions and organophosphates.

PubMed

Tsikas, Dimitrios

2017-02-01

Pentafluorobenzyl bromide (PFB-Br) is a versatile derivatization agent. It is widely used in chromatography and mass spectrometry since several decades. The bromide atom is largely the single leaving group of PFB-Br. It is substituted by wide a spectrum of nucleophiles in aqueous and non-aqueous systems to form electrically neutral, in most organic solvents soluble, generally thermally stable, volatile, strongly electron-capturing and ultraviolet light-absorbing derivatives. Because of these greatly favoured physicochemical properties, PFB-Br emerged an ideal derivatization agent for highly sensitive analysis of endogenous and exogenous substances including various inorganic and organic anions by electron capture detection or after electron-capture negative-ion chemical ionization in GC-MS. The present article attempts an appraisal of the utility of PFB-Br in analytical chemistry. It reviews and discusses papers dealing with the use of PFB-Br as the derivatization reagent in the qualitative and quantitative analysis of endogenous and exogenous inorganic anions in various biological samples, notably plasma, urine and saliva. These analytes include nitrite, nitrate, cyanide and dialkyl organophosphates. Special emphasis is given to mass spectrometry-based approaches and stable-isotope dilution techniques. Copyright © 2016 Elsevier B.V. All rights reserved.

Predictive Analytical Model for Isolator Shock-Train Location in a Mach 2.2 Direct-Connect Supersonic Combustion Tunnel

NASA Astrophysics Data System (ADS)

Lingren, Joe; Vanstone, Leon; Hashemi, Kelley; Gogineni, Sivaram; Donbar, Jeffrey; Akella, Maruthi; Clemens, Noel

2016-11-01

This study develops an analytical model for predicting the leading shock of a shock-train in the constant area isolator section in a Mach 2.2 direct-connect scramjet simulation tunnel. The effective geometry of the isolator is assumed to be a weakly converging duct owing to boundary-layer growth. For some given pressure rise across the isolator, quasi-1D equations relating to isentropic or normal shock flows can be used to predict the normal shock location in the isolator. The surface pressure distribution through the isolator was measured during experiments and both the actual and predicted locations can be calculated. Three methods of finding the shock-train location are examined, one based on the measured pressure rise, one using a non-physics-based control model, and one using the physics-based analytical model. It is shown that the analytical model performs better than the non-physics-based model in all cases. The analytic model is less accurate than the pressure threshold method but requires significantly less information to compute. In contrast to other methods for predicting shock-train location, this method is relatively accurate and requires as little as a single pressure measurement. This makes this method potentially useful for unstart control applications.

EPA Science Matters Newsletter: Chemical Warfare Agent Analytical Standards Facilitate Lab Testing (Published November 2013)

EPA Pesticide Factsheets

Learn about the EPA chemists' efforts to develop methods for detecting extremely low concentrations of nerve agents, such as sarin, VX, soman and cyclohexyl sarin, and the blister agent sulfur mustard.

A Novel Machine Learning Classifier Based on a Qualia Modeling Agent (QMA)

DTIC Science & Technology

Information Theory (IIT) of Consciousness , which proposes that the fundamental structural elements of consciousness are qualia. By modeling the...This research develops a computational agent, which overcomes this problem. The Qualia Modeling Agent (QMA) is modeled after two cognitive theories

Solution of the spatial neutral model yields new bounds on the Amazonian species richness

NASA Astrophysics Data System (ADS)

Shem-Tov, Yahav; Danino, Matan; Shnerb, Nadav M.

2017-02-01

Neutral models, in which individual agents with equal fitness undergo a birth-death-mutation process, are very popular in population genetics and community ecology. Usually these models are applied to populations and communities with spatial structure, but the analytic results presented so far are limited to well-mixed or mainland-island scenarios. Here we combine analytic results and numerics to obtain an approximate solution for the species abundance distribution and the species richness for the neutral model on continuous landscape. We show how the regional diversity increases when the recruitment length decreases and the spatial segregation of species grows. Our results are supported by extensive numerical simulations and allow one to probe the numerically inaccessible regime of large-scale systems with extremely small mutation/speciation rates. Model predictions are compared with the findings of recent large-scale surveys of tropical trees across the Amazon basin, yielding new bounds for the species richness (between 13100 and 15000) and the number of singleton species (between 455 and 690).

Cost-Effectiveness of Antibiotic Prophylaxis Strategies for Transrectal Prostate Biopsy in an Era of Increasing Antimicrobial Resistance.

PubMed

Lee, Kyueun; Drekonja, Dimitri M; Enns, Eva A

2018-03-01

To determine the optimal antibiotic prophylaxis strategy for transrectal prostate biopsy (TRPB) as a function of the local antibiotic resistance profile. We developed a decision-analytic model to assess the cost-effectiveness of four antibiotic prophylaxis strategies: ciprofloxacin alone, ceftriaxone alone, ciprofloxacin and ceftriaxone in combination, and directed prophylaxis selection based on susceptibility testing. We used a payer's perspective and estimated the health care costs and quality-adjusted life-years (QALYs) associated with each strategy for a cohort of 66-year-old men undergoing TRPB. Costs and benefits were discounted at 3% annually. Base-case resistance prevalence was 29% to ciprofloxacin and 7% to ceftriaxone, reflecting susceptibility patterns observed at the Minneapolis Veterans Affairs Health Care System. Resistance levels were varied in sensitivity analysis. In the base case, single-agent prophylaxis strategies were dominated. Directed prophylaxis strategy was the optimal strategy at a willingness-to-pay threshold of $50,000/QALY gained. Relative to the directed prophylaxis strategy, the incremental cost-effectiveness ratio of the combination strategy was $123,333/QALY gained over the lifetime time horizon. In sensitivity analysis, single-agent prophylaxis strategies were preferred only at extreme levels of resistance. Directed or combination prophylaxis strategies were optimal for a wide range of resistance levels. Facilities using single-agent antibiotic prophylaxis strategies before TRPB should re-evaluate their strategies unless extremely low levels of antimicrobial resistance are documented. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Surface Analysis of Nerve Agent Degradation Products by ...

EPA Pesticide Factsheets

Report This sampling and analytical procedure was developed and applied by a single laboratory to investigate nerve agent degradation products, which may persist at a contaminated site, via surface wiping followed by analytical characterization. The performance data presented demonstrate the fitness-for-purpose regarding surface analysis in that single laboratory. Surfaces (laminate, glass, galvanized steel, vinyl tile, painted drywall and treated wood) were wiped with cotton gauze wipes, sonicated, extracted with distilled water, and filtered. Samples were analyzed with direct injection electrospray ionization liquid chromatography tandem mass spectrometry (ESI-LC/MS/MS) without derivatization. Detection limit data were generated for all analytes of interest on a laminate surface. Accuracy and precision data were generated from each surface fortified with these analytes.

Strategy selection in the minority game

NASA Astrophysics Data System (ADS)

D'hulst, R.; Rodgers, G. J.

2000-04-01

We investigate the dynamics of the choice of an active strategy in the minority game. A history distribution is introduced as an analytical tool to study the asymmetry between the two choices offered to the agents. Its properties are studied numerically. It allows us to show that the departure from uniformity in the initial attribution of strategies to the agents is important even in the efficient market. Also, an approximate expression for the variance of the number of agents at one side in the efficient phase is proposed. All the analytical propositions are supported by numerical simulations of the system.

A Multiagent Based Model for Tactical Planning

DTIC Science & Technology

2002-10-01

Pub. Co. 1985. [10] Castillo, J.M. Aproximación mediante procedimientos de Inteligencia Artificial al planeamiento táctico. Doctoral Thesis...been developed under the same conceptual model and using similar Artificial Intelligence Tools. We use four different stimulus/response agents in...The conceptual model is built on base of the Agents theory. To implement the different agents we have used Artificial Intelligence techniques such

Lapse of time effects on tax evasion in an agent-based econophysics model

NASA Astrophysics Data System (ADS)

Seibold, Götz; Pickhardt, Michael

2013-05-01

We investigate an inhomogeneous Ising model in the context of tax evasion dynamics where different types of agents are parameterized via local temperatures and magnetic fields. In particular, we analyze the impact of lapse of time effects (i.e. backauditing) and endogenously determined penalty rates on tax compliance. Both features contribute to a microfoundation of agent-based econophysics models of tax evasion.

Self-organized cooperative behavior and critical penalty in an evolving population

NASA Astrophysics Data System (ADS)

Xu, Chen; Hui, P. M.; Yu, You-Yang; Gu, Guo-Qing

2009-10-01

The emergence of cooperation and the effectiveness of penalties among competing agents are studied via a model of evolutionary game incorporating adaptive behavior and penalties for illegal acts. For initially identical agents, a phase diagram is obtained via an analytic approach, with results in good agreement with numerical simulations. The results show that there exists a critical penalty for achieving a completely honest population and a sufficiently well-behaved initial population requires no penalty. Self-organized segregation to extreme actions emerges in the dynamics for a system with uniformly distributed initial tendencies for cooperation. After training, the penalty can be relaxed without ruining the adapted cooperative behavior. Results of our model in a population taking on the form of a 2D square lattice are also reported.

Investigation of the Persistence of Nerve Agent Degradation ...

EPA Pesticide Factsheets

Journal Article The persistence of chemical warfare nerve agent degradation analytes on surfaces is important for reasons ranging from indicating the presence of nerve agent on that surface to environmental restoration of a site after nerve agent release. This study investigates the persistence of several chemical warfare nerve agent degradation analytes on a number of indoor surfaces and presents an approach for wipe sampling of surfaces, followed by wipe extraction and liquid chromatography-tandem mass spectrometry detection. Multiple commercially available wipe materials were investigated to determine optimal wipe recoveries. Tested surfaces, including several porous/permeable and largely nonporous/impermeable surfaces, were investigated to determine recoveries from these indoor surface materials. Wipe extracts were analyzed by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and compared with high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) results. UPLC provides a sensitive separation of targeted degradation analytes in addition to being nearly four times faster than HPLC, allowing for greater throughput during a widespread release concerning large-scale contamination and subsequent remediation events. Percent recoveries from nonporous/impermeable surfaces were 60-103% for isopropyl methylphosphonate (IMPA), 61-91 % for ethyl methylphosphonate (EMPA), and 60-98% for pinacolyl methylphosphona

A structurally based analytic model of growth and biomass dynamics in single species stands of conifers

Treesearch

Robin J. Tausch

2015-01-01

A theoretically based analytic model of plant growth in single species conifer communities based on the species fully occupying a site and fully using the site resources is introduced. Model derivations result in a single equation simultaneously describes changes over both, different site conditions (or resources available), and over time for each variable for each...

Agent-Based Modeling of Growth Processes

ERIC Educational Resources Information Center

Abraham, Ralph

2014-01-01

Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

Antibodies and antibody-derived analytical biosensors

PubMed Central

Sharma, Shikha; Byrne, Hannah

2016-01-01

The rapid diagnosis of many diseases and timely initiation of appropriate treatment are critical determinants that promote optimal clinical outcomes and general public health. Biosensors are now being applied for rapid diagnostics due to their capacity for point-of-care use with minimum need for operator input. Antibody-based biosensors or immunosensors have revolutionized diagnostics for the detection of a plethora of analytes such as disease markers, food and environmental contaminants, biological warfare agents and illicit drugs. Antibodies are ideal biorecognition elements that provide sensors with high specificity and sensitivity. This review describes monoclonal and recombinant antibodies and different immobilization approaches crucial for antibody utilization in biosensors. Examples of applications of a variety of antibody-based sensor formats are also described. PMID:27365031

From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling

ERIC Educational Resources Information Center

Sengupta, Pratim; Farris, Amy Voss; Wright, Mason

2012-01-01

Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research…

Modelling of robotic work cells using agent based-approach

NASA Astrophysics Data System (ADS)

Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

2016-08-01

In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors.

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Access Control for Cooperation Systems Based on Group Situation

NASA Astrophysics Data System (ADS)

Kim, Minsoo; Joshi, James B. D.; Kim, Minkoo

Cooperation systems characterize many emerging environments such as ubiquitous and pervasive systems. Agent based cooperation systems have been proposed in the literature to address challenges of such emerging application environments. A key aspect of such agent based cooperation system is the group situation that changes dynamically and governs the requirements of the cooperation. While individual agent context is important, the overall cooperation behavior is more driven by the group context because of relationships and interactions between agents. Dynamic access control based on group situation is a crucial challenge in such cooperation systems. In this paper we propose a dynamic role based access control model for cooperation systems based on group situation. The model emphasizes capability based agent to role mapping and group situation based permission assignment to allow capturing dynamic access policies that evolve continuously.

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Recent progress in econophysics: Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

NASA Astrophysics Data System (ADS)

Xin, Chen; Huang, Ji-Ping

2017-12-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like "intelligence" remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents' intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Kinetic theory of situated agents applied to pedestrian flow in a corridor

NASA Astrophysics Data System (ADS)

Rangel-Huerta, A.; Muñoz-Meléndez, A.

2010-03-01

A situated agent-based model for simulation of pedestrian flow in a corridor is presented. In this model, pedestrians choose their paths freely and make decisions based on local criteria for solving collision conflicts. The crowd consists of multiple walking agents equipped with a function of perception as well as a competitive rule-based strategy that enables pedestrians to reach free access areas. Pedestrians in our model are autonomous entities capable of perceiving and making decisions. They apply socially accepted conventions, such as avoidance rules, as well as individual preferences such as the use of specific exit points, or the execution of eventual comfort turns resulting in spontaneous changes of walking speed. Periodic boundary conditions were considered in order to determine the density-average walking speed, and the density-average activity with respect to specific parameters: comfort angle turn and frequency of angle turn of walking agents. The main contribution of this work is an agent-based model where each pedestrian is represented as an autonomous agent. At the same time the pedestrian crowd dynamics is framed by the kinetic theory of biological systems.

An agent-based computational model for tuberculosis spreading on age-structured populations

NASA Astrophysics Data System (ADS)

Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

2015-06-01

In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Reverse engineering a social agent-based hidden markov model--visage.

PubMed

Chen, Hung-Ching Justin; Goldberg, Mark; Magdon-Ismail, Malik; Wallace, William A

2008-12-01

We present a machine learning approach to discover the agent dynamics that drives the evolution of the social groups in a community. We set up the problem by introducing an agent-based hidden Markov model for the agent dynamics: an agent's actions are determined by micro-laws. Nonetheless, We learn the agent dynamics from the observed communications without knowing state transitions. Our approach is to identify the appropriate micro-laws corresponding to an identification of the appropriate parameters in the model. The model identification problem is then formulated as a mixed optimization problem. To solve the problem, we develop a multistage learning process for determining the group structure, the group evolution, and the micro-laws of a community based on the observed set of communications among actors, without knowing the semantic contents. Finally, to test the quality of our approximations and the feasibility of the approach, we present the results of extensive experiments on synthetic data as well as the results on real communities, such as Enron email and Movie newsgroups. Insight into agent dynamics helps us understand the driving forces behind social evolution.

The Interactive Minority Game: a Web-based investigation of human market interactions

NASA Astrophysics Data System (ADS)

Laureti, Paolo; Ruch, Peter; Wakeling, Joseph; Zhang, Yi-Cheng

2004-01-01

The unprecedented access offered by the World Wide Web brings with it the potential to gather huge amounts of data on human activities. Here we exploit this by using a toy model of financial markets, the Minority Game (MG), to investigate human speculative trading behaviour and information capacity. Hundreds of individuals have played a total of tens of thousands of game turns against computer-controlled agents in the Web-based Interactive Minority Game. The analytical understanding of the MG permits fine-tuning of the market situations encountered, allowing for investigation of human behaviour in a variety of controlled environments. In particular, our results indicate a transition in players’ decision-making, as the markets become more difficult, between deductive behaviour making use of short-term trends in the market, and highly repetitive behaviour that ignores entirely the market history, yet outperforms random decision-making.

Big data analytics as a service infrastructure: challenges, desired properties and solutions

NASA Astrophysics Data System (ADS)

Martín-Márquez, Manuel

2015-12-01

CERN's accelerator complex generates a very large amount of data. A large volumen of heterogeneous data is constantly generated from control equipment and monitoring agents. These data must be stored and analysed. Over the decades, CERN's researching and engineering teams have applied different approaches, techniques and technologies for this purpose. This situation has minimised the necessary collaboration and, more relevantly, the cross data analytics over different domains. These two factors are essential to unlock hidden insights and correlations between the underlying processes, which enable better and more efficient daily-based accelerator operations and more informed decisions. The proposed Big Data Analytics as a Service Infrastructure aims to: (1) integrate the existing developments; (2) centralise and standardise the complex data analytics needs for CERN's research and engineering community; (3) deliver real-time, batch data analytics and information discovery capabilities; and (4) provide transparent access and Extract, Transform and Load (ETL), mechanisms to the various and mission-critical existing data repositories. This paper presents the desired objectives and properties resulting from the analysis of CERN's data analytics requirements; the main challenges: technological, collaborative and educational and; potential solutions.

A physically based analytical spatial air temperature and humidity model

Treesearch

Yang Yang; Theodore A. Endreny; David J. Nowak

2013-01-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat...

Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

NASA Technical Reports Server (NTRS)

Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

2004-01-01

These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

Analytical performance specifications for changes in assay bias (Δbias) for data with logarithmic distributions as assessed by effects on reference change values.

PubMed

Petersen, Per H; Lund, Flemming; Fraser, Callum G; Sölétormos, György

2016-11-01

Background The distributions of within-subject biological variation are usually described as coefficients of variation, as are analytical performance specifications for bias, imprecision and other characteristics. Estimation of specifications required for reference change values is traditionally done using relationship between the batch-related changes during routine performance, described as Δbias, and the coefficients of variation for analytical imprecision (CV A ): the original theory is based on standard deviations or coefficients of variation calculated as if distributions were Gaussian. Methods The distribution of between-subject biological variation can generally be described as log-Gaussian. Moreover, recent analyses of within-subject biological variation suggest that many measurands have log-Gaussian distributions. In consequence, we generated a model for the estimation of analytical performance specifications for reference change value, with combination of Δbias and CV A based on log-Gaussian distributions of CV I as natural logarithms. The model was tested using plasma prolactin and glucose as examples. Results Analytical performance specifications for reference change value generated using the new model based on log-Gaussian distributions were practically identical with the traditional model based on Gaussian distributions. Conclusion The traditional and simple to apply model used to generate analytical performance specifications for reference change value, based on the use of coefficients of variation and assuming Gaussian distributions for both CV I and CV A , is generally useful.

Chronic Heart Failure Follow-up Management Based on Agent Technology

PubMed Central

Safdari, Reza

2015-01-01

Objectives Monitoring heart failure patients through continues assessment of sign and symptoms by information technology tools lead to large reduction in re-hospitalization. Agent technology is one of the strongest artificial intelligence areas; therefore, it can be expected to facilitate, accelerate, and improve health services especially in home care and telemedicine. The aim of this article is to provide an agent-based model for chronic heart failure (CHF) follow-up management. Methods This research was performed in 2013-2014 to determine appropriate scenarios and the data required to monitor and follow-up CHF patients, and then an agent-based model was designed. Results Agents in the proposed model perform the following tasks: medical data access, communication with other agents of the framework and intelligent data analysis, including medical data processing, reasoning, negotiation for decision-making, and learning capabilities. Conclusions The proposed multi-agent system has ability to learn and thus improve itself. Implementation of this model with more and various interval times at a broader level could achieve better results. The proposed multi-agent system is no substitute for cardiologists, but it could assist them in decision-making. PMID:26618038

Foundations of “new” social science: Institutional legitimacy from philosophy, complexity science, postmodernism, and agent-based modeling

PubMed Central

Henrickson, Leslie; McKelvey, Bill

2002-01-01

Since the death of positivism in the 1970s, philosophers have turned their attention to scientific realism, evolutionary epistemology, and the Semantic Conception of Theories. Building on these trends, Campbellian Realism allows social scientists to accept real-world phenomena as criterion variables against which theories may be tested without denying the reality of individual interpretation and social construction. The Semantic Conception reduces the importance of axioms, but reaffirms the role of models and experiments. Philosophers now see models as “autonomous agents” that exert independent influence on the development of a science, in addition to theory and data. The inappropriate molding effects of math models on social behavior modeling are noted. Complexity science offers a “new” normal science epistemology focusing on order creation by self-organizing heterogeneous agents and agent-based models. The more responsible core of postmodernism builds on the idea that agents operate in a constantly changing web of interconnections among other agents. The connectionist agent-based models of complexity science draw on the same conception of social ontology as do postmodernists. These recent developments combine to provide foundations for a “new” social science centered on formal modeling not requiring the mathematical assumptions of agent homogeneity and equilibrium conditions. They give this “new” social science legitimacy in scientific circles that current social science approaches lack. PMID:12011408

Market-oriented Programming Using Small-world Networks for Controlling Building Environments

NASA Astrophysics Data System (ADS)

Shigei, Noritaka; Miyajima, Hiromi; Osako, Tsukasa

The market model, which is one of the economic activity models, is modeled as an agent system, and applying the model to the resource allocation problem has been studied. For air conditioning control of building, which is one of the resource allocation problems, an effective method based on the agent system using auction has been proposed for traditional PID controller. On the other hand, it has been considered that this method is performed by decentralized control. However, its decentralization is not perfect, and its performace is not enough. In this paper, firstly, we propose a perfectly decentralized agent model and show its performance. Secondly, in order to improve the model, we propose the agent model based on small-world model. The effectiveness of the proposed model is shown by simulation.

Multiple piezo-patch energy harvesters integrated to a thin plate with AC-DC conversion: analytical modeling and numerical validation

NASA Astrophysics Data System (ADS)

Aghakhani, Amirreza; Basdogan, Ipek; Erturk, Alper

2016-04-01

Plate-like components are widely used in numerous automotive, marine, and aerospace applications where they can be employed as host structures for vibration based energy harvesting. Piezoelectric patch harvesters can be easily attached to these structures to convert the vibrational energy to the electrical energy. Power output investigations of these harvesters require accurate models for energy harvesting performance evaluation and optimization. Equivalent circuit modeling of the cantilever-based vibration energy harvesters for estimation of electrical response has been proposed in recent years. However, equivalent circuit formulation and analytical modeling of multiple piezo-patch energy harvesters integrated to thin plates including nonlinear circuits has not been studied. In this study, equivalent circuit model of multiple parallel piezoelectric patch harvesters together with a resistive load is built in electronic circuit simulation software SPICE and voltage frequency response functions (FRFs) are validated using the analytical distributedparameter model. Analytical formulation of the piezoelectric patches in parallel configuration for the DC voltage output is derived while the patches are connected to a standard AC-DC circuit. The analytic model is based on the equivalent load impedance approach for piezoelectric capacitance and AC-DC circuit elements. The analytic results are validated numerically via SPICE simulations. Finally, DC power outputs of the harvesters are computed and compared with the peak power amplitudes in the AC output case.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

ERIC Educational Resources Information Center

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Mathematical modeling of malaria infection with innate and adaptive immunity in individuals and agent-based communities.

PubMed

Gurarie, David; Karl, Stephan; Zimmerman, Peter A; King, Charles H; St Pierre, Timothy G; Davis, Timothy M E

2012-01-01

Agent-based modeling of Plasmodium falciparum infection offers an attractive alternative to the conventional Ross-Macdonald methodology, as it allows simulation of heterogeneous communities subjected to realistic transmission (inoculation patterns). We developed a new, agent based model that accounts for the essential in-host processes: parasite replication and its regulation by innate and adaptive immunity. The model also incorporates a simplified version of antigenic variation by Plasmodium falciparum. We calibrated the model using data from malaria-therapy (MT) studies, and developed a novel calibration procedure that accounts for a deterministic and a pseudo-random component in the observed parasite density patterns. Using the parasite density patterns of 122 MT patients, we generated a large number of calibrated parameters. The resulting data set served as a basis for constructing and simulating heterogeneous agent-based (AB) communities of MT-like hosts. We conducted several numerical experiments subjecting AB communities to realistic inoculation patterns reported from previous field studies, and compared the model output to the observed malaria prevalence in the field. There was overall consistency, supporting the potential of this agent-based methodology to represent transmission in realistic communities. Our approach represents a novel, convenient and versatile method to model Plasmodium falciparum infection.

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Simplified analytical model and balanced design approach for light-weight wood-based structural panel in bending

Treesearch

Jinghao Li; John F. Hunt; Shaoqin Gong; Zhiyong Cai

2016-01-01

This paper presents a simplified analytical model and balanced design approach for modeling lightweight wood-based structural panels in bending. Because many design parameters are required to input for the model of finite element analysis (FEA) during the preliminary design process and optimization, the equivalent method was developed to analyze the mechanical...

Examining the Impact of the Walking School Bus With an Agent-Based Model

PubMed Central

Diez-Roux, Ana; Evenson, Kelly R.; Colabianchi, Natalie

2014-01-01

We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness. PMID:24832410

Strategy evolution driven by switching probabilities in structured multi-agent systems

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Chen, Zengqiang; Li, Zhiqi

2017-10-01

Evolutionary mechanism driving the commonly seen cooperation among unrelated individuals is puzzling. Related models for evolutionary games on graphs traditionally assume that players imitate their successful neighbours with higher benefits. Notably, an implicit assumption here is that players are always able to acquire the required pay-off information. To relax this restrictive assumption, a contact-based model has been proposed, where switching probabilities between strategies drive the strategy evolution. However, the explicit and quantified relation between a player's switching probability for her strategies and the number of her neighbours remains unknown. This is especially a key point in heterogeneously structured system, where players may differ in the numbers of their neighbours. Focusing on this, here we present an augmented model by introducing an attenuation coefficient and evaluate its influence on the evolution dynamics. Results show that the individual influence on others is negatively correlated with the contact numbers specified by the network topologies. Results further provide the conditions under which the coexisting strategies can be calculated analytically.

Navigating the Perfect Storm: Research Strategies for Socialecological Systems in a Rapidly Evolving World

NASA Astrophysics Data System (ADS)

Dearing, John A.; Bullock, Seth; Costanza, Robert; Dawson, Terry P.; Edwards, Mary E.; Poppy, Guy M.; Smith, Graham M.

2012-04-01

The `Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

Quantitative evaluation of analyte transport on microfluidic paper-based analytical devices (μPADs).

PubMed

Ota, Riki; Yamada, Kentaro; Suzuki, Koji; Citterio, Daniel

2018-02-07

The transport efficiency during capillary flow-driven sample transport on microfluidic paper-based analytical devices (μPADs) made from filter paper has been investigated for a selection of model analytes (Ni 2+ , Zn 2+ , Cu 2+ , PO 4 3- , bovine serum albumin, sulforhodamine B, amaranth) representing metal cations, complex anions, proteins and anionic molecules. For the first time, the transport of the analytical target compounds rather than the sample liquid, has been quantitatively evaluated by means of colorimetry and absorption spectrometry-based methods. The experiments have revealed that small paperfluidic channel dimensions, additional user operation steps (e.g. control of sample volume, sample dilution, washing step) as well as the introduction of sample liquid wicking areas allow to increase analyte transport efficiency. It is also shown that the interaction of analytes with the negatively charged cellulosic paper substrate surface is strongly influenced by the physico-chemical properties of the model analyte and can in some cases (Cu 2+ ) result in nearly complete analyte depletion during sample transport. The quantitative information gained through these experiments is expected to contribute to the development of more sensitive μPADs.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

Using Model Replication to Improve the Reliability of Agent-Based Models

NASA Astrophysics Data System (ADS)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

An Agent Based Collaborative Simplification of 3D Mesh Model

NASA Astrophysics Data System (ADS)

Wang, Li-Rong; Yu, Bo; Hagiwara, Ichiro

Large-volume mesh model faces the challenge in fast rendering and transmission by Internet. The current mesh models obtained by using three-dimensional (3D) scanning technology are usually very large in data volume. This paper develops a mobile agent based collaborative environment on the development platform of mobile-C. Communication among distributed agents includes grasping image of visualized mesh model, annotation to grasped image and instant message. Remote and collaborative simplification can be efficiently conducted by Internet.

Determining the Antifungal Agent Clioquinol by HPLC, the Not so Pure Preparation: A Laboratory-Based Case Study for an Instrumental Analytical Chemistry Course

ERIC Educational Resources Information Center

Schaber, Peter M.; Hobika, Geoffrey

2018-01-01

The case study approach provides students with a better appreciation of how scientists solve problems and conduct themselves in the "real world". When applied to the undergraduate chemistry laboratory, this approach also challenges critical thinking skills and creativity in ways "cook book" experiments very often do not. This…

New York State energy-analytic information system: first-stage implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allentuck, J.; Carroll, O.; Fiore, L.

1979-09-01

So that energy policy by state government may be formulated within the constraints imposed by policy determined at the national level - yet reflect the diverse interests of its citizens - large quantities of data and sophisticated analytic capabilities are required. This report presents the design of an energy-information/analytic system for New York State, the data for a base year, 1976, and projections of these data. At the county level, 1976 energy-supply demand data and electric generating plant data are provided as well. Data-base management is based on System 2000. Three computerized models provide the system's basic analytic capacity. Themore » Brookhaven Energy System Network Simulator provides an integrating framework while a price-response model and a weather sensitive energy demand model furnished a short-term energy response estimation capability. The operation of these computerized models is described. 62 references, 25 figures, 39 tables.« less

'Power base' tactics for workplace change - an interview study with industrial engineers and ergonomists.

PubMed

Berlin, Cecilia; Neumann, W Patrick; Theberge, Nancy; Örtengren, Roland

2017-05-01

The work activities of industrial engineers (IEs) and ergonomists drive workplace changes. The purpose of this study is to compare the work practices of the two professions and examine (1) how IEs and ergonomists gain influence over workplace changes and (2) whether there are prevailing types of intentional interaction behaviours called Power bases (PB) present in the interaction tactics they employ. The study identified key behavioural strategies used by the interviewees to successfully influence workplace changes; these were then mapped to their corresponding PB. Results showed that IEs and ergonomists were successfully influencing workplace changes using several tactics across the spectrum of PB, with the exception of Reward and Coercion. The study concludes with a list of recommended workplace change agent tactics, and proposes that a PB 'analytical lens' can serve to increase the budding ergonomists' critical and analytical skills when considering possible workplace change tactics. Practitioner Summary: This interview study examines how workplace ergonomics change agents, represented by the two professions: industrial engineers and ergonomists, perceive and exercise their capacity to influence workplace change. Key behavioural tactics that interviewees have found successful are reported, alongside effects on short- and long-term relations with other workplace-influencing stakeholders.

PHARMACEUTICAL AND BIOMEDICAL APPLICATIONS OF AFFINITY CHROMATOGRAPHY: RECENT TRENDS AND DEVELOPMENTS

PubMed Central

Hage, David S.; Anguizola, Jeanethe A.; Bi, Cong; Li, Rong; Matsuda, Ryan; Papastavros, Efthimia; Pfaunmiller, Erika; Vargas, John; Zheng, Xiwei

2012-01-01

Affinity chromatography is a separation technique that has become increasingly important in work with biological samples and pharmaceutical agents. This method is based on the use of a biologically-related agent as a stationary phase to selectively retain analytes or to study biological interactions. This review discusses the basic principles behind affinity chromatography and examines recent developments that have occurred in the use of this method for biomedical and pharmaceutical analysis. Techniques based on traditional affinity supports are discussed, but an emphasis is placed on methods in which affinity columns are used as part of HPLC systems or in combination with other analytical methods. General formats for affinity chromatography that are considered include step elution schemes, weak affinity chromatography, affinity extraction and affinity depletion. Specific separation techniques that are examined include lectin affinity chromatography, boronate affinity chromatography, immunoaffinity chromatography, and immobilized metal ion affinity chromatography. Approaches for the study of biological interactions by affinity chromatography are also presented, such as the measurement of equilibrium constants, rate constants, or competition and displacement effects. In addition, related developments in the use of immobilized enzyme reactors, molecularly imprinted polymers, dye ligands and aptamers are briefly considered. PMID:22305083

SYN-JEM: A Quantitative Job-Exposure Matrix for Five Lung Carcinogens.

PubMed

Peters, Susan; Vermeulen, Roel; Portengen, Lützen; Olsson, Ann; Kendzia, Benjamin; Vincent, Raymond; Savary, Barbara; Lavoué, Jérôme; Cavallo, Domenico; Cattaneo, Andrea; Mirabelli, Dario; Plato, Nils; Fevotte, Joelle; Pesch, Beate; Brüning, Thomas; Straif, Kurt; Kromhout, Hans

2016-08-01

The use of measurement data in occupational exposure assessment allows more quantitative analyses of possible exposure-response relations. We describe a quantitative exposure assessment approach for five lung carcinogens (i.e. asbestos, chromium-VI, nickel, polycyclic aromatic hydrocarbons (by its proxy benzo(a)pyrene (BaP)) and respirable crystalline silica). A quantitative job-exposure matrix (JEM) was developed based on statistical modeling of large quantities of personal measurements. Empirical linear models were developed using personal occupational exposure measurements (n = 102306) from Europe and Canada, as well as auxiliary information like job (industry), year of sampling, region, an a priori exposure rating of each job (none, low, and high exposed), sampling and analytical methods, and sampling duration. The model outcomes were used to create a JEM with a quantitative estimate of the level of exposure by job, year, and region. Decreasing time trends were observed for all agents between the 1970s and 2009, ranging from -1.2% per year for personal BaP and nickel exposures to -10.7% for asbestos (in the time period before an asbestos ban was implemented). Regional differences in exposure concentrations (adjusted for measured jobs, years of measurement, and sampling method and duration) varied by agent, ranging from a factor 3.3 for chromium-VI up to a factor 10.5 for asbestos. We estimated time-, job-, and region-specific exposure levels for four (asbestos, chromium-VI, nickel, and RCS) out of five considered lung carcinogens. Through statistical modeling of large amounts of personal occupational exposure measurement data we were able to derive a quantitative JEM to be used in community-based studies. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

A framework for the use of agent based modeling to simulate ...

EPA Pesticide Factsheets

Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an agent-based model (ABM) is used to simulate population distributions of longitudinal patterns of four macro activities (sleeping, eating, working, and commuting) in populations of adults over a period of one year. In this ABM, an individual is modeled as an agent whose movement through time and space is determined by a set of decision rules. The rules are based on the agent having time-varying “needs” that are satisfied by performing actions. Needs are modeled as increasing over time, and taking an action reduces the need. Need-satisfying actions include sleeping (meeting the need for rest), eating (meeting the need for food), and commuting/working (meeting the need for income). Every time an action is completed, the model determines the next action the agent will take based on the magnitude of each of the agent’s needs at that point in time. Different activities advertise their ability to satisfy various needs of the agent (such as food to eat or sleeping in a bed or on a couch). The model then chooses the activity that satisfies the greatest of the agent’s needs. When multiple actions could address a need, the model will choose the most effective of the actions (bed over the couc

Hybrid evolutionary computing model for mobile agents of wireless Internet multimedia

NASA Astrophysics Data System (ADS)

Hortos, William S.

2001-03-01

The ecosystem is used as an evolutionary paradigm of natural laws for the distributed information retrieval via mobile agents to allow the computational load to be added to server nodes of wireless networks, while reducing the traffic on communication links. Based on the Food Web model, a set of computational rules of natural balance form the outer stage to control the evolution of mobile agents providing multimedia services with a wireless Internet protocol WIP. The evolutionary model shows how mobile agents should behave with the WIP, in particular, how mobile agents can cooperate, compete and learn from each other, based on an underlying competition for radio network resources to establish the wireless connections to support the quality of service QoS of user requests. Mobile agents are also allowed to clone themselves, propagate and communicate with other agents. A two-layer model is proposed for agent evolution: the outer layer is based on the law of natural balancing, the inner layer is based on a discrete version of a Kohonen self-organizing feature map SOFM to distribute network resources to meet QoS requirements. The former is embedded in the higher OSI layers of the WIP, while the latter is used in the resource management procedures of Layer 2 and 3 of the protocol. Algorithms for the distributed computation of mobile agent evolutionary behavior are developed by adding a learning state to the agent evolution state diagram. When an agent is in an indeterminate state, it can communicate to other agents. Computing models can be replicated from other agents. Then the agents transitions to the mutating state to wait for a new information-retrieval goal. When a wireless terminal or station lacks a network resource, an agent in the suspending state can change its policy to submit to the environment before it transitions to the searching state. The agents learn the facts of agent state information entered into an external database. In the cloning process, two agents on a host station sharing a common goal can be merged or married to compose a new agent. Application of the two-layer set of algorithms for mobile agent evolution, performed in a distributed processing environment, is made to the QoS management functions of the IP multimedia IM sub-network of the third generation 3G Wideband Code-division Multiple Access W-CDMA wireless network.

A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department.

PubMed

Wilk, S; Michalowski, W; O'Sullivan, D; Farion, K; Sayyad-Shirabad, J; Kuziemsky, C; Kukawka, B

2013-01-01

The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.

Agent Based Modeling Applications for Geosciences

NASA Astrophysics Data System (ADS)

Stein, J. S.

2004-12-01

Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in a thermodynamic framework as a set of reactions that roll-up the integrated effect that diverse biological communities exert on a geological system. This approach may work well to predict the effect of certain biological communities in specific environments in which experimental data is available. However, it does not further our knowledge of how the geobiological system actually functions on a micro scale. Agent-based techniques may provide a framework to explore the fundamental interactions required to explain the system-wide behavior. This presentation will present a survey of several promising applications of agent-based modeling approaches to problems in the geosciences and describe specific contributions to some of the inherent challenges facing this approach.

Information accumulation system by inheritance and diffusion

NASA Astrophysics Data System (ADS)

Shin, J. K.

2009-09-01

This paper suggests a new model, called as the IAS (Information Accumulation System), for the description of the dynamic process that people use to accumulate their information (knowledge or opinion) for specific issues. Using the concept of information, both the internal and the external mechanism of the opinion dynamics are treated on a unified frame. The information is quantified as a real number with fixed bounds. New concepts, such as inheritance and differential absorption, are incorporated in IAS in addition to the conventional diffusive interaction between people. Thus, the dynamics of the IAS are governed by following three factors: inheritance rate, diffusivity and absorption rate. The original set of equations was solved with an agent based modeling technique. In addition, the individual equations for each of the agents were assembled and transformed into a set of equations for the ensemble averages, which are greatly reduced in number and can be solved analytically. The example simulations showed interesting results such as the critical behavior with respect to diffusivity, the information polarization out of zero-sum news and the dependence of the solutions on the initial conditions alone. The results were speculated in relation to today’s modern society where the diffusivity of information has been greatly increased through the internet and mobile phones.

A knowledge base architecture for distributed knowledge agents

NASA Technical Reports Server (NTRS)

Riedesel, Joel; Walls, Bryan

1990-01-01

A tuple space based object oriented model for knowledge base representation and interpretation is presented. An architecture for managing distributed knowledge agents is then implemented within the model. The general model is based upon a database implementation of a tuple space. Objects are then defined as an additional layer upon the database. The tuple space may or may not be distributed depending upon the database implementation. A language for representing knowledge and inference strategy is defined whose implementation takes advantage of the tuple space. The general model may then be instantiated in many different forms, each of which may be a distinct knowledge agent. Knowledge agents may communicate using tuple space mechanisms as in the LINDA model as well as using more well known message passing mechanisms. An implementation of the model is presented describing strategies used to keep inference tractable without giving up expressivity. An example applied to a power management and distribution network for Space Station Freedom is given.

Brahms Mobile Agents: Architecture and Field Tests

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Kaskiris, Charis; vanHoof, Ron

2002-01-01

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called agents, implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., return here later and bring this back to the habitat ). This combination of agents, rover, and model-based spoken dialogue interface constitutes a personal assistant. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system.

An equation-free approach to agent-based computation: Bifurcation analysis and control of stationary states

NASA Astrophysics Data System (ADS)

Siettos, C. I.; Gear, C. W.; Kevrekidis, I. G.

2012-08-01

We show how the equation-free approach can be exploited to enable agent-based simulators to perform system-level computations such as bifurcation, stability analysis and controller design. We illustrate these tasks through an event-driven agent-based model describing the dynamic behaviour of many interacting investors in the presence of mimesis. Using short bursts of appropriately initialized runs of the detailed, agent-based simulator, we construct the coarse-grained bifurcation diagram of the (expected) density of agents and investigate the stability of its multiple solution branches. When the mimetic coupling between agents becomes strong enough, the stable stationary state loses its stability at a coarse turning point bifurcation. We also demonstrate how the framework can be used to design a wash-out dynamic controller that stabilizes open-loop unstable stationary states even under model uncertainty.

IPA (v1): a framework for agent-based modelling of soil water movement

NASA Astrophysics Data System (ADS)

Mewes, Benjamin; Schumann, Andreas H.

2018-06-01

In the last decade, agent-based modelling (ABM) became a popular modelling technique in social sciences, medicine, biology, and ecology. ABM was designed to simulate systems that are highly dynamic and sensitive to small variations in their composition and their state. As hydrological systems, and natural systems in general, often show dynamic and non-linear behaviour, ABM can be an appropriate way to model these systems. Nevertheless, only a few studies have utilized the ABM method for process-based modelling in hydrology. The percolation of water through the unsaturated soil is highly responsive to the current state of the soil system; small variations in composition lead to major changes in the transport system. Hence, we present a new approach for modelling the movement of water through a soil column: autonomous water agents that transport water through the soil while interacting with their environment as well as with other agents under physical laws.

An Immune Agent for Web-Based AI Course

ERIC Educational Resources Information Center

Gong, Tao; Cai, Zixing

2006-01-01

To overcome weakness and faults of a web-based e-learning course such as Artificial Intelligence (AI), an immune agent was proposed, simulating a natural immune mechanism against a virus. The immune agent was built on the multi-dimension education agent model and immune algorithm. The web-based AI course was comprised of many files, such as HTML…

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

Cascading Walks Model for Human Mobility Patterns

PubMed Central

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Background Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. Methodology/Principal Findings In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Conclusions/Significance Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns. PMID:25860140

Cascading walks model for human mobility patterns.

PubMed

Han, Xiao-Pu; Wang, Xiang-Wen; Yan, Xiao-Yong; Wang, Bing-Hong

2015-01-01

Uncovering the mechanism behind the scaling laws and series of anomalies in human trajectories is of fundamental significance in understanding many spatio-temporal phenomena. Recently, several models, e.g. the explorations-returns model (Song et al., 2010) and the radiation model for intercity travels (Simini et al., 2012), have been proposed to study the origin of these anomalies and the prediction of human movements. However, an agent-based model that could reproduce most of empirical observations without priori is still lacking. In this paper, considering the empirical findings on the correlations of move-lengths and staying time in human trips, we propose a simple model which is mainly based on the cascading processes to capture the human mobility patterns. In this model, each long-range movement activates series of shorter movements that are organized by the law of localized explorations and preferential returns in prescribed region. Based on the numerical simulations and analytical studies, we show more than five statistical characters that are well consistent with the empirical observations, including several types of scaling anomalies and the ultraslow diffusion properties, implying the cascading processes associated with the localized exploration and preferential returns are indeed a key in the understanding of human mobility activities. Moreover, the model shows both of the diverse individual mobility and aggregated scaling displacements, bridging the micro and macro patterns in human mobility. In summary, our model successfully explains most of empirical findings and provides deeper understandings on the emergence of human mobility patterns.

Solution to the problem of interferences in electrochemical sensors using the fill-and-flow channel biosensor.

PubMed

Zhao, Min; Hibbert, D Brynn; Gooding, J Justin

2003-02-01

A generic fill-and-flow channel biosensor with upstream electrodes to determine the extent of interferences in the sample is described. A pair of upstream electrodes poised at a suitable potential allows both the calculation of the extent of removal of interfering agents and the effect of interfering agents at the detector electrode. A model was developed and tested that predicts the concentrations of all species throughout the channel and, hence, the current at each electrode due to each species. This enables correction of the detector electrode current and a more accurate determination of the analyte concentration. The concept was applied to a biosensor for the determination of glucose in the presence of ascorbic acid, acetamidophenol, and uric acid, as well as glucose in wine samples containing polyphenolic interfering agents.

What Protein Charging (and Supercharging) Reveal about the Mechanism of Electrospray Ionization

PubMed Central

Loo, Rachel R. Ogorzalek; Lakshmanan, Rajeswari

2014-01-01

Understanding the charging mechanism of electrospray ionization is central to overcoming shortcomings such as ion suppression or limited dynamic range and explaining phenomena such as supercharging. Towards that end, we explore what accumulated observations reveal about the mechanism of electrospray. We introduce the idea of an intermediate region for electrospray ionization (and other ionization methods) to account for the facts that solution charge state distributions (CSDs) do not correlate to those observed by ESI– MS (the latter bear more charge) and that gas phase reactions can reduce, but not increase the extent of charging. This region incorporates properties, e.g., basicities, intermediate between solution and gas phase. Assuming that droplet species polarize within the high electric field leads to equations describing ion emission resembling those from the equilibrium partitioning model. The equations predict many trends successfully, including CSD shifts to higher m/z for concentrated analytes and shifts to lower m/z for sprays employing smaller emitter opening diameters. From this view, a single mechanism can be formulated to explain how reagents that promote analyte charging (“supercharging”) such as m–NBA, sulfolane, and 3–nitrobenzonitrile increase analyte charge from “denaturing” and “native” solvent systems. It is suggested that additives’ Brønsted basicities are inversely correlated to their ability to shift CSDs to lower m/z in positive ESI, as are Brønsted acidities for negative ESI. Because supercharging agents reduce an analyte's solution ionization, excess spray charge is bestowed on evaporating ions carryingfewer opposing charges. Brønsted basicity (or acidity) determines how much ESI charge is lost to the agent (unavailable to evaporating analyte). PMID:25135609

Diversity and Community: The Role of Agent-Based Modeling.

PubMed

Stivala, Alex

2017-06-01

Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity-community dialectic, some with the aid of agent-based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent-based modeling and the real-world concerns of community psychology. © Society for Community Research and Action 2017.

Application of a Genetic Algorithm and Multi Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the Workplace

DTIC Science & Technology

2008-06-01

postponed the fulfillment of her own Masters Degree by at least 18 months so that I would have the opportunity to earn mine. She is smart , lovely...GENETIC ALGORITHM AND MULTI AGENT SYSTEM TO EXPLORE EMERGENT PATTERNS OF SOCIAL RATIONALITY AND A DISTRESS-BASED MODEL FOR DECEIT IN THE WORKPLACE...of a Genetic Algorithm and Mutli Agent System to Explore Emergent Patterns of Social Rationality and a Distress-Based Model for Deceit in the

Stability of subsystem solutions in agent-based models

NASA Astrophysics Data System (ADS)

Perc, Matjaž

2018-01-01

The fact that relatively simple entities, such as particles or neurons, or even ants or bees or humans, give rise to fascinatingly complex behaviour when interacting in large numbers is the hallmark of complex systems science. Agent-based models are frequently employed for modelling and obtaining a predictive understanding of complex systems. Since the sheer number of equations that describe the behaviour of an entire agent-based model often makes it impossible to solve such models exactly, Monte Carlo simulation methods must be used for the analysis. However, unlike pairwise interactions among particles that typically govern solid-state physics systems, interactions among agents that describe systems in biology, sociology or the humanities often involve group interactions, and they also involve a larger number of possible states even for the most simplified description of reality. This begets the question: when can we be certain that an observed simulation outcome of an agent-based model is actually stable and valid in the large system-size limit? The latter is key for the correct determination of phase transitions between different stable solutions, and for the understanding of the underlying microscopic processes that led to these phase transitions. We show that a satisfactory answer can only be obtained by means of a complete stability analysis of subsystem solutions. A subsystem solution can be formed by any subset of all possible agent states. The winner between two subsystem solutions can be determined by the average moving direction of the invasion front that separates them, yet it is crucial that the competing subsystem solutions are characterised by a proper composition and spatiotemporal structure before the competition starts. We use the spatial public goods game with diverse tolerance as an example, but the approach has relevance for a wide variety of agent-based models.

Label-free optical resonant sensors for biochemical applications

NASA Astrophysics Data System (ADS)

Ciminelli, Caterina; Campanella, Clarissa Martina; Dell'Olio, Francesco; Campanella, Carlo Edoardo; Armenise, Mario Nicola

2013-03-01

For a number of years, the scientific community has been paying growing attention to the monitoring and enhancement of public health and the quality of life through the detection of all dangerous agents for the human body, including gases, proteins, virus, and bacterial agents. When these agents are detected through label-free biochemical sensors, the molecules are not modified structurally or functionally by adding fluorescent or radioactive dyes. This work focuses on label-free optical ring resonator-based configurations suited for bio-chemical sensing, highlighting their physical aspects and specific applications. Resonant wavelength shift and the modal splitting occurring when the analyte interacts with microresonant structures are the two major physical aspects analyzed in this paper. Competitive optical platforms proposed in the literature are also illustrated together with their properties and performance.

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

Hierarchical extreme learning machine based reinforcement learning for goal localization

NASA Astrophysics Data System (ADS)

AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini

2017-03-01

The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.

Contamination in food from packaging material.

PubMed

Lau, O W; Wong, S K

2000-06-16

Packaging has become an indispensible element in the food manufacturing process, and different types of additives, such as antioxidants, stabilizers, lubricants, anti-static and anti-blocking agents, have also been developed to improve the performance of polymeric packaging materials. Recently the packaging has been found to represent a source of contamination itself through the migration of substances from the packaging into food. Various analytical methods have been developed to analyze the migrants in the foodstuff, and migration evaluation procedures based on theoretical prediction of migration from plastic food contact material were also introduced recently. In this paper, the regulatory control, analytical methodology, factors affecting the migration and migration evaluation are reviewed.

Development of agent-based on-line adaptive signal control (ASC) framework using connected vehicle (CV) technology.

DOT National Transportation Integrated Search

2016-04-01

In this study, we developed an adaptive signal control (ASC) framework for connected vehicles (CVs) using agent-based modeling technique. : The proposed framework consists of two types of agents: 1) vehicle agents (VAs); and 2) signal controller agen...

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav

2010-01-01

Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

Comparison of thermal analytic model with experimental test results for 30-sentimeter-diameter engineering model mercury ion thruster

NASA Technical Reports Server (NTRS)

Oglebay, J. C.

1977-01-01

A thermal analytic model for a 30-cm engineering model mercury-ion thruster was developed and calibrated using the experimental test results of tests of a pre-engineering model 30-cm thruster. A series of tests, performed later, simulated a wide range of thermal environments on an operating 30-cm engineering model thruster, which was instrumented to measure the temperature distribution within it. The modified analytic model is described and analytic and experimental results compared for various operating conditions. Based on the comparisons, it is concluded that the analytic model can be used as a preliminary design tool to predict thruster steady-state temperature distributions for stage and mission studies and to define the thermal interface bewteen the thruster and other elements of a spacecraft.

Organization-based Model-driven Development of High-assurance Multiagent Systems

DTIC Science & Technology

2009-02-27

based Model -driven Development of High-assurance Multiagent Systems " performed by Dr. Scott A . DeLoach and Dr Robby at Kansas State University... A Capabilities Based Model for Artificial Organizations. Journal of Autonomous Agents and Multiagent Systems . Volume 16, no. 1, February 2008, pp...Matson, E . T. (2007). A capabilities based theory of artificial organizations. Journal of Autonomous Agents and Multiagent Systems

Characterization of chemical agent transport in paints.

PubMed

Willis, Matthew P; Gordon, Wesley; Lalain, Teri; Mantooth, Brent

2013-09-15

A combination of vacuum-based vapor emission measurements with a mass transport model was employed to determine the interaction of chemical warfare agents with various materials, including transport parameters of agents in paints. Accurate determination of mass transport parameters enables the simulation of the chemical agent distribution in a material for decontaminant performance modeling. The evaluation was performed with the chemical warfare agents bis(2-chloroethyl) sulfide (distilled mustard, known as the chemical warfare blister agent HD) and O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioate (VX), an organophosphate nerve agent, deposited on to two different types of polyurethane paint coatings. The results demonstrated alignment between the experimentally measured vapor emission flux and the predicted vapor flux. Mass transport modeling demonstrated rapid transport of VX into the coatings; VX penetrated through the aliphatic polyurethane-based coating (100 μm) within approximately 107 min. By comparison, while HD was more soluble in the coatings, the penetration depth in the coatings was approximately 2× lower than VX. Applications of mass transport parameters include the ability to predict agent uptake, and subsequent long-term vapor emission or contact transfer where the agent could present exposure risks. Additionally, these parameters and model enable the ability to perform decontamination modeling to predict how decontaminants remove agent from these materials. Published by Elsevier B.V.

Improved partition equilibrium model for predicting analyte response in electrospray ionization mass spectrometry.

PubMed

Du, Lihong; White, Robert L

2009-02-01

A previously proposed partition equilibrium model for quantitative prediction of analyte response in electrospray ionization mass spectrometry is modified to yield an improved linear relationship. Analyte mass spectrometer response is modeled by a competition mechanism between analyte and background electrolytes that is based on partition equilibrium considerations. The correlation between analyte response and solution composition is described by the linear model over a wide concentration range and the improved model is shown to be valid for a wide range of experimental conditions. The behavior of an analyte in a salt solution, which could not be explained by the original model, is correctly predicted. The ion suppression effects of 16:0 lysophosphatidylcholine (LPC) on analyte signals are attributed to a combination of competition for excess charge and reduction of total charge due to surface tension effects. In contrast to the complicated mathematical forms that comprise the original model, the simplified model described here can more easily be employed to predict analyte mass spectrometer responses for solutions containing multiple components. Copyright (c) 2008 John Wiley & Sons, Ltd.

Fertility treatment in women with polycystic ovary syndrome: a decision analysis of different oral ovulation induction agents

PubMed Central

Jungheim, Emily S.; Odibo, Anthony O.

2010-01-01

Study objective To compare different oral ovulation induction agents in treating infertile women with polycystic ovary syndrome Design Decision-analytic model comparing three treatment strategies using probability estimates derived from literature review and sensitivity analyses performed on the baseline assumptions Setting Outpatient reproductive medicine and gynecology practices Patients Infertile women with polycystic ovary syndrome Interventions Metformin, clomiphene citrate, or metformin with clomiphene citrate Main Outcome Measures Live birth Results Within the baseline assumptions, combination therapy with metformin and clomiphene citrate was the preferred therapy for achieving live birth in women with polycystic ovary syndrome. Sensitivity analysis revealed the model to be robust over a wide range of probabilities. Conclusions Combination therapy with metformin and clomiphene citrate should be considered as first-line treatment for infertile women with polycystic ovary syndrome PMID:20451181

Driving-forces model on individual behavior in scenarios considering moving threat agents

NASA Astrophysics Data System (ADS)

Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia

2017-09-01

The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.

A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

EPA Science Inventory

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

Enabling private and public sector organizations as agents of homeland security

NASA Astrophysics Data System (ADS)

Glassco, David H. J.; Glassco, Jordan C.

2006-05-01

Homeland security and defense applications seek to reduce the risk of undesirable eventualities across physical space in real-time. With that functional requirement in mind, our work focused on the development of IP based agent telecommunication solutions for heterogeneous sensor / robotic intelligent "Things" that could be deployed across the internet. This paper explains how multi-organization information and device sharing alliances may be formed to enable organizations to act as agents of homeland security (in addition to other uses). Topics include: (i) using location-aware, agent based, real-time information sharing systems to integrate business systems, mobile devices, sensor and actuator based devices and embedded devices used in physical infrastructure assets, equipment and other man-made "Things"; (ii) organization-centric real-time information sharing spaces using on-demand XML schema formatted networks; (iii) object-oriented XML serialization as a methodology for heterogeneous device glue code; (iv) how complex requirements for inter / intra organization information and device ownership and sharing, security and access control, mobility and remote communication service, tailored solution life cycle management, service QoS, service and geographic scalability and the projection of remote physical presence (through sensing and robotics) and remote informational presence (knowledge of what is going elsewhere) can be more easily supported through feature inheritance with a rapid agent system development methodology; (v) how remote object identification and tracking can be supported across large areas; (vi) how agent synergy may be leveraged with analytics to complement heterogeneous device networks.

Evaluating the effect of human activity patterns on air pollution exposure using an integrated field-based and agent-based modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; Beelen, Rob M. J.; de Bakker, Merijn P.; Karssenberg, Derek

2015-04-01

Constructing spatio-temporal numerical models to support risk assessment, such as assessing the exposure of humans to air pollution, often requires the integration of field-based and agent-based modelling approaches. Continuous environmental variables such as air pollution are best represented using the field-based approach which considers phenomena as continuous fields having attribute values at all locations. When calculating human exposure to such pollutants it is, however, preferable to consider the population as a set of individuals each with a particular activity pattern. This would allow to account for the spatio-temporal variation in a pollutant along the space-time paths travelled by individuals, determined, for example, by home and work locations, road network, and travel times. Modelling this activity pattern requires an agent-based or individual based modelling approach. In general, field- and agent-based models are constructed with the help of separate software tools, while both approaches should play together in an interacting way and preferably should be combined into one modelling framework, which would allow for efficient and effective implementation of models by domain specialists. To overcome this lack in integrated modelling frameworks, we aim at the development of concepts and software for an integrated field-based and agent-based modelling framework. Concepts merging field- and agent-based modelling were implemented by extending PCRaster (http://www.pcraster.eu), a field-based modelling library implemented in C++, with components for 1) representation of discrete, mobile, agents, 2) spatial networks and algorithms by integrating the NetworkX library (http://networkx.github.io), allowing therefore to calculate e.g. shortest routes or total transport costs between locations, and 3) functions for field-network interactions, allowing to assign field-based attribute values to networks (i.e. as edge weights), such as aggregated or averaged concentration values. We demonstrate the approach by using six land use regression (LUR) models developed in the ESCAPE (European Study of Cohorts for Air Pollution Effects) project. These models calculate several air pollutants (e.g. NO2, NOx, PM2.5) for the entire Netherlands at a high (5 m) resolution. Using these air pollution maps, we compare exposure of individuals calculated at their x, y location of their home, their work place, and aggregated over the close surroundings of these locations. In addition, total exposure is accumulated over daily activity patterns, summing exposure at home, at the work place, and while travelling between home and workplace, by routing individuals over the Dutch road network, using the shortest route. Finally, we illustrate how routes can be calculated with the minimum total exposure (instead of shortest distance).

Petri Nets as Modeling Tool for Emergent Agents

NASA Technical Reports Server (NTRS)

Bergman, Marto

2004-01-01

Emergent agents, those agents whose local interactions can cause unexpected global results, require a method of modeling that is both dynamic and structured Petri Nets, a modeling tool developed for dynamic discrete event system of mainly functional agents, provide this, and have the benefit of being an established tool. We present here the details of the modeling method here and discuss how to implement its use for modeling agent-based systems. Petri Nets have been used extensively in the modeling of functional agents, those agents who have defined purposes and whose actions should result in a know outcome. However, emergent agents, those agents who have a defined structure but whose interaction causes outcomes that are unpredictable, have not yet found a modeling style that suits them. A problem with formally modeling emergent agents that any formal modeling style usually expects to show the results of a problem and the results of problems studied using emergent agents are not apparent from the initial construction. However, the study of emergent agents still requires a method to analyze the agents themselves, and have sensible conversation about the differences and similarities between types of emergent agents. We attempt to correct this problem by applying Petri Nets to the characterization of emergent agents. In doing so, the emergent properties of these agents can be highlighted, and conversation about the nature and compatibility of the differing methods of agent creation can begin.

A hybrid analytical model for open-circuit field calculation of multilayer interior permanent magnet machines

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Xia, Changliang; Yan, Yan; Geng, Qiang; Shi, Tingna

2017-08-01

Due to the complicated rotor structure and nonlinear saturation of rotor bridges, it is difficult to build a fast and accurate analytical field calculation model for multilayer interior permanent magnet (IPM) machines. In this paper, a hybrid analytical model suitable for the open-circuit field calculation of multilayer IPM machines is proposed by coupling the magnetic equivalent circuit (MEC) method and the subdomain technique. In the proposed analytical model, the rotor magnetic field is calculated by the MEC method based on the Kirchhoff's law, while the field in the stator slot, slot opening and air-gap is calculated by subdomain technique based on the Maxwell's equation. To solve the whole field distribution of the multilayer IPM machines, the coupled boundary conditions on the rotor surface are deduced for the coupling of the rotor MEC and the analytical field distribution of the stator slot, slot opening and air-gap. The hybrid analytical model can be used to calculate the open-circuit air-gap field distribution, back electromotive force (EMF) and cogging torque of multilayer IPM machines. Compared with finite element analysis (FEA), it has the advantages of faster modeling, less computation source occupying and shorter time consuming, and meanwhile achieves the approximate accuracy. The analytical model is helpful and applicable for the open-circuit field calculation of multilayer IPM machines with any size and pole/slot number combination.

Agent-Based Models in Empirical Social Research

ERIC Educational Resources Information Center

Bruch, Elizabeth; Atwell, Jon

2015-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first…

Model-based Utility Functions

NASA Astrophysics Data System (ADS)

Hibbard, Bill

2012-05-01

Orseau and Ring, as well as Dewey, have recently described problems, including self-delusion, with the behavior of agents using various definitions of utility functions. An agent's utility function is defined in terms of the agent's history of interactions with its environment. This paper argues, via two examples, that the behavior problems can be avoided by formulating the utility function in two steps: 1) inferring a model of the environment from interactions, and 2) computing utility as a function of the environment model. Basing a utility function on a model that the agent must learn implies that the utility function must initially be expressed in terms of specifications to be matched to structures in the learned model. These specifications constitute prior assumptions about the environment so this approach will not work with arbitrary environments. But the approach should work for agents designed by humans to act in the physical world. The paper also addresses the issue of self-modifying agents and shows that if provided with the possibility to modify their utility functions agents will not choose to do so, under some usual assumptions.

Remote Agent Demonstration

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Kurien, James; Rajan, Kanna

1999-01-01

We describe the computer demonstration of the Remote Agent Experiment (RAX). The Remote Agent is a high-level, model-based, autonomous control agent being validated on the NASA Deep Space 1 spacecraft.

Spreading of nonmotile bacteria on a hard agar plate: Comparison between agent-based and stochastic simulations

NASA Astrophysics Data System (ADS)

Rana, Navdeep; Ghosh, Pushpita; Perlekar, Prasad

2017-11-01

We study spreading of a nonmotile bacteria colony on a hard agar plate by using agent-based and continuum models. We show that the spreading dynamics depends on the initial nutrient concentration, the motility, and the inherent demographic noise. Population fluctuations are inherent in an agent-based model, whereas for the continuum model we model them by using a stochastic Langevin equation. We show that the intrinsic population fluctuations coupled with nonlinear diffusivity lead to a transition from a diffusion limited aggregation type of morphology to an Eden-like morphology on decreasing the initial nutrient concentration.

Toward Agent-Based Models of the Development And Evolution of Business Relations and Networks

NASA Astrophysics Data System (ADS)

Wilkinson, Ian F.; Marks, Robert E.; Young, Louise

Firms achieve competitive advantage in part through the development of cooperative relations with other firms and organisations. We describe a program of research designed to map and model the development of cooperative inter-firm relations, including the processes and paths by which firms may evolve from adversarial to more cooperative relations. Narrative-event-history methods will be used to develop stylised histories of the emergence of business relations in various contexts and to identify relevant causal mechanisms to be included in the agent-based models of relationship and network evolution. The relationship histories will provide the means of assuring the agent-based models developed.

A biolayer interferometry-based assay for rapid and highly sensitive detection of biowarfare agents.

PubMed

Mechaly, Adva; Cohen, Hila; Cohen, Ofer; Mazor, Ohad

2016-08-01

Biolayer interferometry (BLI) is an optical technique that uses fiber-optic biosensors for label-free real-time monitoring of protein-protein interactions. In this study, we coupled the advantages of the Octet Red BLI system (automation, fluidics-free, and on-line monitoring) with a signal enhancement step and developed a rapid and sensitive immunological-based method for detection of biowarfare agents. As a proof of concept, we chose to demonstrate the efficacy of this novel assay for the detection of agents representing two classes of biothreats, proteinaceous toxins, and bacterial pathogens: ricin, a lethal plant toxin, and the gram-negative bacterium Francisella tularensis, the causative agent of tularemia. The assay setup consisted of biotinylated antibodies immobilized to the biosensor coupled with alkaline phosphatase-labeled antibodies as the detection moiety to create nonsoluble substrate crystals that precipitate on the sensor surface, thereby inducing a significant wavelength interference. It was found that this BLI-based assay enables sensitive detection of these pathogens (detection limits of 10 pg/ml and 1 × 10(4) pfu/ml ricin and F. tularensis, respectively) within a very short time frame (17 min). Owing to its simplicity, this assay can be easily adapted to detect other analytes in general, and biowarfare agents in particular, in a rapid and sensitive manner. Copyright © 2016 Elsevier Inc. All rights reserved.

Agent-based game theory modeling for driverless vehicles at intersections.

DOT National Transportation Integrated Search

2013-02-01

This report presents three research efforts that were published in various journals. The first research effort presents a reactive-driving agent based algorithm for modeling driver left turn gap acceptance behavior at signalized intersections. This m...

Constructing Agent Model for Virtual Training Systems

NASA Astrophysics Data System (ADS)

Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

A fuzzy logic control in adjustable autonomy of a multi-agent system for an automated elderly movement monitoring application.

PubMed

Mostafa, Salama A; Mustapha, Aida; Mohammed, Mazin Abed; Ahmad, Mohd Sharifuddin; Mahmoud, Moamin A

2018-04-01

Autonomous agents are being widely used in many systems, such as ambient assisted-living systems, to perform tasks on behalf of humans. However, these systems usually operate in complex environments that entail uncertain, highly dynamic, or irregular workload. In such environments, autonomous agents tend to make decisions that lead to undesirable outcomes. In this paper, we propose a fuzzy-logic-based adjustable autonomy (FLAA) model to manage the autonomy of multi-agent systems that are operating in complex environments. This model aims to facilitate the autonomy management of agents and help them make competent autonomous decisions. The FLAA model employs fuzzy logic to quantitatively measure and distribute autonomy among several agents based on their performance. We implement and test this model in the Automated Elderly Movements Monitoring (AEMM-Care) system, which uses agents to monitor the daily movement activities of elderly users and perform fall detection and prevention tasks in a complex environment. The test results show that the FLAA model improves the accuracy and performance of these agents in detecting and preventing falls. Copyright © 2018 Elsevier B.V. All rights reserved.

Bouchaud-Mézard model on a random network

NASA Astrophysics Data System (ADS)

Ichinomiya, Takashi

2012-09-01

We studied the Bouchaud-Mézard (BM) model, which was introduced to explain Pareto's law in a real economy, on a random network. Using “adiabatic and independent” assumptions, we analytically obtained the stationary probability distribution function of wealth. The results show that wealth condensation, indicated by the divergence of the variance of wealth, occurs at a larger J than that obtained by the mean-field theory, where J represents the strength of interaction between agents. We compared our results with numerical simulation results and found that they were in good agreement.

Distributed Cooperation Solution Method of Complex System Based on MAS

NASA Astrophysics Data System (ADS)

Weijin, Jiang; Yuhui, Xu

To adapt the model in reconfiguring fault diagnosing to dynamic environment and the needs of solving the tasks of complex system fully, the paper introduced multi-Agent and related technology to the complicated fault diagnosis, an integrated intelligent control system is studied in this paper. Based on the thought of the structure of diagnostic decision and hierarchy in modeling, based on multi-layer decomposition strategy of diagnosis task, a multi-agent synchronous diagnosis federation integrated different knowledge expression modes and inference mechanisms are presented, the functions of management agent, diagnosis agent and decision agent are analyzed, the organization and evolution of agents in the system are proposed, and the corresponding conflict resolution algorithm in given, Layered structure of abstract agent with public attributes is build. System architecture is realized based on MAS distributed layered blackboard. The real world application shows that the proposed control structure successfully solves the fault diagnose problem of the complex plant, and the special advantage in the distributed domain.

Low-picomolar, label-free procalcitonin analytical detection with an electrolyte-gated organic field-effect transistor based electronic immunosensor.

PubMed

Seshadri, Preethi; Manoli, Kyriaki; Schneiderhan-Marra, Nicole; Anthes, Uwe; Wierzchowiec, Piotr; Bonrad, Klaus; Di Franco, Cinzia; Torsi, Luisa

2018-05-01

Herein a label-free immunosensor based on electrolyte-gated organic field-effect transistor (EGOFET) was developed for the detection of procalcitonin (PCT), a sepsis marker. Antibodies specific to PCT were immobilized on the poly-3-hexylthiophene (P3HT) organic semiconductor surface through direct physical adsorption followed by a post-treatment with bovine serum albumin (BSA) which served as the blocking agent to prevent non-specific adsorption. Antibodies together with BSA (forming the whole biorecognition layer) served to selectively capture the procalcitonin target analyte. The entire immunosensor fabrication process was fast, requiring overall 45min to be completed before analyte sensing. The EGOFET immunosensor showed excellent electrical properties, comparable to those of bare P3HT based EGOFET confirming reliable biosensing with bio-functional EGOFET immunosensor. The detection limit of the immunosensor was as low as 2.2pM and within a range of clinical relevance. The relative standard deviation of the individual calibration data points, measured on immunosensors fabricated on different chips (reproducibility error) was below 7%. The developed immunosensor showed high selectivity to the PCT analyte which was evident through control experiments. This report of PCT detection is first of its kind among the electronic sensors based on EGOFETs. The developed sensor is versatile and compatible with low-cost fabrication techniques. Copyright © 2017 Elsevier B.V. All rights reserved.

Applications of Aptamers as Sensors

NASA Astrophysics Data System (ADS)

Cho, Eun Jeong; Lee, Joo-Woon; Ellington, Andrew D.

2009-07-01

Aptamers are ligand-binding nucleic acids whose affinities and selectivities can rival those of antibodies. They have been adapted to analytical applications not only as alternatives to antibodies, but as unique reagents in their own right. In particular, aptamers can be readily site-specifically modified during chemical or enzymatic synthesis to incorporate particular reporters, linkers, or other moieties. Also, aptamer secondary structures can be engineered to undergo analyte-dependent conformational changes, which, in concert with the ability to specifically place chemical agents, opens up a wealth of possible signal transduction schemas, irrespective of whether the detection modality is optical, electrochemical, or mass based. Finally, because aptamers are nucleic acids, they are readily adapted to sequence- (and hence signal-) amplification methods. However, application of aptamers without a basic knowledge of their biochemistry or technical requirements can cause serious analytical difficulties.

Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

Source-term development for a contaminant plume for use by multimedia risk assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whelan, Gene; McDonald, John P.; Taira, Randal Y.

1999-12-01

Multimedia modelers from the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE) are collaborating to conduct a comprehensive and quantitative benchmarking analysis of four intermedia models: DOE's Multimedia Environmental Pollutant Assessment System (MEPAS), EPA's MMSOILS, EPA's PRESTO, and DOE's RESidual RADioactivity (RESRAD). These models represent typical analytically, semi-analytically, and empirically based tools that are utilized in human risk and endangerment assessments for use at installations containing radioactive and/or hazardous contaminants. Although the benchmarking exercise traditionally emphasizes the application and comparison of these models, the establishment of a Conceptual Site Model (CSM) should be viewed with equalmore » importance. This paper reviews an approach for developing a CSM of an existing, real-world, Sr-90 plume at DOE's Hanford installation in Richland, Washington, for use in a multimedia-based benchmarking exercise bet ween MEPAS, MMSOILS, PRESTO, and RESRAD. In an unconventional move for analytically based modeling, the benchmarking exercise will begin with the plume as the source of contamination. The source and release mechanism are developed and described within the context of performing a preliminary risk assessment utilizing these analytical models. By beginning with the plume as the source term, this paper reviews a typical process and procedure an analyst would follow in developing a CSM for use in a preliminary assessment using this class of analytical tool.« less

Enhancement of the conductivity detection signal in capillary electrophoresis systems using neutral cyclodextrins as sweeping agents.

PubMed

Boublík, Milan; Riesová, Martina; Dubský, Pavel; Gaš, Bohuslav

2018-06-01

Conductivity detection is a universal detection technique often encountered in electrophoretic separation systems, especially in modern chip-electrophoresis based devices. On the other hand, it is sparsely combined with another contemporary trend of enhancing limits of detection by means of various preconcentration strategies. This can be attributed to the fact that a preconcentration experimental setup usually brings about disturbances in a conductivity baseline. Sweeping with a neutral sweeping agent seems a good candidate for overcoming this problem. A neutral sweeping agent does not hinder the conductivity detection while a charged analyte may preconcentrate on its boundary due to a decrease in its effective mobility. This study investigates such sweeping systems theoretically, by means of computer simulations, and experimentally. A formula is provided for the reliable estimation of the preconcentration factor. Additionally, it is demonstrated that the conductivity signal can significantly benefit from slowing down the analyte and thus the overall signal enhancement can easily overweight amplification caused solely by the sweeping process. The overall enhancement factor can be deduced a priori from the linearized theory of electrophoresis implemented in the PeakMaster freeware. Sweeping by neutral cyclodextrin is demonstrated on an amplification of a conductivity signal of flurbiprofen in a real drug sample. Finally, a possible formation of unexpected system peaks in systems with a neutral sweeping agent is revealed by the computer simulation and confirmed experimentally. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dual quantification of dapivirine and maraviroc in cervicovaginal secretions from ophthalmic tear strips and polyester-based swabs via liquid chromatographic-tandem mass spectrometric (LC-MS/MS) analysis.

PubMed

Parsons, Teresa L; Emory, Joshua F; Seserko, Lauren A; Aung, Wutyi S; Marzinke, Mark A

2014-09-01

Topical microbicidal agents are being actively pursued as a modality to prevent HIV viral transmission during sexual intercourse. Quantification of antiretroviral agents in specimen sources where antiviral activity is elicited is critical, and drug measurements in cervicovaginal fluid can provide key information on local drug concentrations. Two antiretroviral drugs, dapivirine and maraviroc, have gained interest as vaginal microbicidal agents, and rugged methods are required for their quantification in cervicovaginal secretions. Cervicovaginal fluid spiked with dapivirine and maraviroc were applied to ophthalmic tear strips or polyester-based swabs to mimic collection procedures used in clinical studies. Following sample extraction and the addition of isotopically labeled internal standards, samples were subjected to liquid chromatographic-tandem mass spectrometric (LC-MS/MS) analysis using a Waters BEH C8, 50mm×2.1mm, 1.7μm particle size column, on an API 4000 mass analyzer operated in selective reaction monitoring mode. The method was validated according to FDA Bioanalytical Method Validation guidelines. Due to the disparate saturation capacity of the tested collection devices, the analytical measuring ranges for dapivirine and maravirocin cervicovaginal fluid on the ophthalmic tear strip were 0.05-25ng/tear strip, and 0.025-25ng/tear strip, respectively. As for the polyester-based swab, the analytical measuring ranges were 0.25-125ng/swab for dapivirine and 0.125-125ng/swab for maraviroc. Dilutional studies were performed for both analytes to extended ranges of 25,000ng/tear strip and 11,250ng/swab. Standard curves were generated via weighted (1/x(2)) linear or quadratic regression of calibrators. Precision, accuracy, stability and matrix effects studies were all performed and deemed acceptable according to the recommendations of the FDA Bioanalytical Method Validation guidelines. A rugged LC-MS/MS method for the dual quantification of dapivirine and maraviroc in cervicovaginal fluid using two unique collection devices has been developed and validated. The described method meets the criteria to support large research trials. Copyright © 2014 Elsevier B.V. All rights reserved.

Dual Quantification of Dapivirine and Maraviroc in Cervicovaginal Secretions from Ophthalmic Tear Strips and Polyester-Based Swabs via Liquid Chromatographic-Tandem Mass Spectrometric (LC-MS/MS) Analysis

PubMed Central

Parsons, Teresa L.; Emory, Joshua F.; Seserko, Lauren A.; Aung, Wutyi S.; Marzinke, Mark A.

2014-01-01

Background Topical microbicidal agents are being actively pursued as a modality to prevent HIV viral transmission during sexual intercourse. Quantification of antiretroviral agents in specimen sources where antiviral activity is elicited is critical, and drug measurements in cervicovaginal fluid can provide key information on local drug concentrations. Two antiretroviral drugs, dapivirine and maraviroc, have gained interest as vaginal microbicidal agents, and rugged methods are required for their quantification in cervicovaginal secretions. Methods Cervicovaginal fluid spiked with dapivirine and maraviroc were applied to ophthalmic tear strips or polyester-based swabs to mimic collection procedures used in clinical studies. Following sample extraction and the addition of isotopically-labeled internal standards, samples were subjected to liquid chromatographic-tandem mass spectrometric (LC-MS/MS) analysis using a Waters BEH C8, 50 × 2.1 mm, 1.7 µm particle size column, on an API 4000 mass analyzer operated in selective reaction monitoring mode. The method was validated according to FDA Bioanalytical Method Validation guidelines. Results Due to the disparate saturation capacity of the tested collection devices, the analytical measuring ranges for dapivirine and maravirocin cervicovaginal fluid on the ophthalmic tear strip were 0.05 to 25 ng/tear strip, and 0.025 to 25 ng/tear strip, respectively. As for the polyester-based swab, the analytical measuring ranges were 0.25 to 125 ng/swab for dapivirine and 0.125 to 125 ng/swab for maraviroc. Dilutional studies were performed for both analytes to extended ranges of 25,000 ng/tear strip and 11,250 ng/swab. Standard curves were generated via weighted (1/x2) linear or quadratic regression of calibrators. Precision, accuracy, stability and matrix effects studies were all performed and deemed acceptable according to the recommendations of the FDA Bioanalytical Method Validation guidelines. Conclusions A rugged LC-MS/MS method for the dual quantification of dapivirine and maraviroc in cervicovaginal fluid using two unique collection devices has been developed and validated. The described method meets the criteria to support large research trials. PMID:25005891

Interactions between self-assembled monolayers and an organophosphonate: A detailed study using surface acoustic wave-based mass analysis, polarization modulation-FTIR spectroscopy, and ellipsometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crooks, R.M.; Yang, H.C.; McEllistrem, L.J.

Self-assembled monolayers (SAMs) having surfaces terminated in the following functional groups: -CH{sub 3}, -OH, -COOH, and (COO{sup -}){sub 2}Cu{sup 2+} (MUA-Cu{sup 2+}) have been prepared and examined as potential chemically sensitive interfaces. Mass measurements made using surface acoustic wave (SAW) devices indicate that these surfaces display different degrees of selectivity and sensitivity to a range of analytes. The response of the MUA-Cu{sup 2+} SAM to the nerve-agent simulant diisopropyl methylphosphonate (DIMP) is particularly intriguing. Exposure of this surface to 50%-of-saturation DIMP yields a surface concentration equivalent to about 20 DIMP monolayers. Such a high surface concentration in equilibrium with amore » much lower-than-saturation vapor pressure has not previously been observed. Newly developed analytical tools have made it possible to measure the infrared spectrum of the chemically receptive surface during analyte dosing. Coupled with in-situ SAW/ellipsometry measurements, which permit simultaneous measurement of mass and thickness with nanogram and Angstrom resolution, respectively, it has been possibly to develop a model for the surface chemistry leading to the unusual behavior of this system. The results indicate that DIMP interacts strongly with surface-confined Cu{sup 2+} adduct that nucleates growth of semi-ordered crystallites having substantially lower vapor pressure than the liquid.« less

An Analytic Hierarchy Process for School Quality and Inspection: Model Development and Application

ERIC Educational Resources Information Center

Al Qubaisi, Amal; Badri, Masood; Mohaidat, Jihad; Al Dhaheri, Hamad; Yang, Guang; Al Rashedi, Asma; Greer, Kenneth

2016-01-01

Purpose: The purpose of this paper is to develop an analytic hierarchy planning-based framework to establish criteria weights and to develop a school performance system commonly called school inspections. Design/methodology/approach: The analytic hierarchy process (AHP) model uses pairwise comparisons and a measurement scale to generate the…

Cultural Geography Modeling and Analysis in Helmand Province

DTIC Science & Technology

2010-10-01

the application of an agent-based model called “Cultural Geography” to represent the civilian populace. This project uses a multi-agent system ...represent the civilian populace. This project uses a multi-agent system consisting of an environment, agents, objects (things), operations that can be...environments[1]. The model is patterned after the conflict eco- system described by Kilcullen[2] in an attempt to capture the complexities of irregular

Formalizing the role of agent-based modeling in causal inference and epidemiology.

PubMed

Marshall, Brandon D L; Galea, Sandro

2015-01-15

Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of an Agent Based Model to Estimate and Reduce Time to Restoration of Storm Induced Power Outages

NASA Astrophysics Data System (ADS)

Walsh, T.; Layton, T.; Mellor, J. E.

2017-12-01

Storm damage to the electric grid impacts 23 million electric utility customers and costs US consumers $119 billion annually. Current restoration techniques rely on the past experiences of emergency managers. There are few analytical simulation and prediction tools available for utility managers to optimize storm recovery and decrease consumer cost, lost revenue and restoration time. We developed an agent based model (ABM) for storm recovery in Connecticut. An ABM is a computer modeling technique comprised of agents who are given certain behavioral rules and operate in a given environment. It allows the user to simulate complex systems by varying user-defined parameters to study emergent, unpredicted behavior. The ABM incorporates the road network and electric utility grid for the state, is validated using actual storm event recoveries and utilizes the Dijkstra routing algorithm to determine the best path for repair crews to travel between outages. The ABM has benefits for both researchers and utility managers. It can simulate complex system dynamics, rank variable importance, find tipping points that could significantly reduce restoration time or costs and test a broad range of scenarios. It is a modular, scalable and adaptable technique that can simulate scenarios in silico to inform emergency managers before and during storm events to optimize restoration strategies and better manage expectations of when power will be restored. Results indicate that total restoration time is strongly dependent on the number of crews. However, there is a threshold whereby more crews will not decrease the restoration time, which depends on the total number of outages. The addition of outside crews is more beneficial for storms with a higher number of outages. The time to restoration increases linearly with increasing repair time, while the travel speed has little overall effect on total restoration time. Crews traveling to the nearest outage reduces the total restoration time, while crews going to the outage with most customers affected increases the overall restoration time but more quickly decreases the customers remaining without power. This model can give utility company managers the ability to optimize their restoration strategies before or during a storm event to reduce restoration times and costs.

CALM: Complex Adaptive System (CAS)-Based Decision Support for Enabling Organizational Change

NASA Astrophysics Data System (ADS)

Adler, Richard M.; Koehn, David J.

Guiding organizations through transformational changes such as restructuring or adopting new technologies is a daunting task. Such changes generate workforce uncertainty, fear, and resistance, reducing morale, focus and performance. Conventional project management techniques fail to mitigate these disruptive effects, because social and individual changes are non-mechanistic, organic phenomena. CALM (for Change, Adaptation, Learning Model) is an innovative decision support system for enabling change based on CAS principles. CALM provides a low risk method for validating and refining change strategies that combines scenario planning techniques with "what-if" behavioral simulation. In essence, CALM "test drives" change strategies before rolling them out, allowing organizations to practice and learn from virtual rather than actual mistakes. This paper describes the CALM modeling methodology, including our metrics for measuring organizational readiness to respond to change and other major CALM scenario elements: prospective change strategies; alternate futures; and key situational dynamics. We then describe CALM's simulation engine for projecting scenario outcomes and its associated analytics. CALM's simulator unifies diverse behavioral simulation paradigms including: adaptive agents; system dynamics; Monte Carlo; event- and process-based techniques. CALM's embodiment of CAS dynamics helps organizations reduce risk and improve confidence and consistency in critical strategies for enabling transformations.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

Economic communication model set

NASA Astrophysics Data System (ADS)

Zvereva, Olga M.; Berg, Dmitry B.

2017-06-01

This paper details findings from the research work targeted at economic communications investigation with agent-based models usage. The agent-based model set was engineered to simulate economic communications. Money in the form of internal and external currencies was introduced into the models to support exchanges in communications. Every model, being based on the general concept, has its own peculiarities in algorithm and input data set since it was engineered to solve the specific problem. Several and different origin data sets were used in experiments: theoretic sets were estimated on the basis of static Leontief's equilibrium equation and the real set was constructed on the basis of statistical data. While simulation experiments, communication process was observed in dynamics, and system macroparameters were estimated. This research approved that combination of an agent-based and mathematical model can cause a synergetic effect.

A carrier-based analytical theory for negative capacitance symmetric double-gate field effect transistors and its simulation verification

NASA Astrophysics Data System (ADS)

Jiang, Chunsheng; Liang, Renrong; Wang, Jing; Xu, Jun

2015-09-01

A carrier-based analytical drain current model for negative capacitance symmetric double-gate field effect transistors (NC-SDG FETs) is proposed by solving the differential equation of the carrier, the Pao-Sah current formulation, and the Landau-Khalatnikov equation. The carrier equation is derived from Poisson’s equation and the Boltzmann distribution law. According to the model, an amplified semiconductor surface potential and a steeper subthreshold slope could be obtained with suitable thicknesses of the ferroelectric film and insulator layer at room temperature. Results predicted by the analytical model agree well with those of the numerical simulation from a 2D simulator without any fitting parameters. The analytical model is valid for all operation regions and captures the transitions between them without any auxiliary variables or functions. This model can be used to explore the operating mechanisms of NC-SDG FETs and to optimize device performance.

Quantitative Agent Based Model of User Behavior in an Internet Discussion Forum

PubMed Central

Sobkowicz, Pawel

2013-01-01

The paper presents an agent based simulation of opinion evolution, based on a nonlinear emotion/information/opinion (E/I/O) individual dynamics, to an actual Internet discussion forum. The goal is to reproduce the results of two-year long observations and analyses of the user communication behavior and of the expressed opinions and emotions, via simulations using an agent based model. The model allowed to derive various characteristics of the forum, including the distribution of user activity and popularity (outdegree and indegree), the distribution of length of dialogs between the participants, their political sympathies and the emotional content and purpose of the comments. The parameters used in the model have intuitive meanings, and can be translated into psychological observables. PMID:24324606

Negative interferences by calcium dobesilate in the detection of five serum analytes involving Trinder reaction-based assays

PubMed Central

Wu, Jie; Zhao, Fang; Xia, Liangyu; Cheng, Xinqi; Liu, Qian; Liu, Li; Xu, Ermu; Qiu, Ling

2018-01-01

Previously, we reported the strong negative interference of calcium dobesilate, a vasoprotective agent, in creatinine assays involving the Trinder reaction. It is hypothesized that a similar effect occurs in the detection of uric acid (UA), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). The interferences of calcium dobesilate during the detection of the five serum analytes were investigated on automated systems/analysers, and the effects were compared among eight different assay systems for each analyte. A calcium dobesilate standard was added into two sets of the blank serum pools of each analyte at final concentrations of 0, 2, 4, 8, 16, 32, and 64 μg/mL. The percentage deviation of each analyte value was calculated between each drug concentration and the drug-free samples. The clinically acceptable error levels for UA, TC, TG, HDL-C, and LDL-C were defined as ±4.87%, ±4.1%, ±9.57%, ±5.61%, and ±5.46%, respectively. The observed interference was concentration dependent for each analyte. In the presence of 16 μg/mL calcium dobesilate, which was within the therapeutic range, all seven Trinder reaction-based UA assay systems, two TG assay systems, two HDL-C assay systems and one TC assay system exhibited negative drug interferences. Calcium dobesilate negatively interferes with the detection of UA, TG, TC, and HDL-C in assay systems based on the Trinder reaction. The effect was most significant in UA and TG detection. PMID:29432460

Agent-based modeling of the spread of influenza-like illness in an emergency department: a simulation study.

PubMed

Laskowski, Marek; Demianyk, Bryan C P; Witt, Julia; Mukhi, Shamir N; Friesen, Marcia R; McLeod, Robert D

2011-11-01

The objective of this paper was to develop an agent-based modeling framework in order to simulate the spread of influenza virus infection on a layout based on a representative hospital emergency department in Winnipeg, Canada. In doing so, the study complements mathematical modeling techniques for disease spread, as well as modeling applications focused on the spread of antibiotic-resistant nosocomial infections in hospitals. Twenty different emergency department scenarios were simulated, with further simulation of four infection control strategies. The agent-based modeling approach represents systems modeling, in which the emergency department was modeled as a collection of agents (patients and healthcare workers) and their individual characteristics, behaviors, and interactions. The framework was coded in C++ using Qt4 libraries running under the Linux operating system. A simple ordinary least squares (OLS) regression was used to analyze the data, in which the percentage of patients that became infected in one day within the simulation was the dependent variable. The results suggest that within the given instance context, patient-oriented infection control policies (alternate treatment streams, masking symptomatic patients) tend to have a larger effect than policies that target healthcare workers. The agent-based modeling framework is a flexible tool that can be made to reflect any given environment; it is also a decision support tool for practitioners and policymakers to assess the relative impact of infection control strategies. The framework illuminates scenarios worthy of further investigation, as well as counterintuitive findings.

Model-Drive Architecture for Agent-Based Systems

NASA Technical Reports Server (NTRS)

Gradanin, Denis; Singh, H. Lally; Bohner, Shawn A.; Hinchey, Michael G.

2004-01-01

The Model Driven Architecture (MDA) approach uses a platform-independent model to define system functionality, or requirements, using some specification language. The requirements are then translated to a platform-specific model for implementation. An agent architecture based on the human cognitive model of planning, the Cognitive Agent Architecture (Cougaar) is selected for the implementation platform. The resulting Cougaar MDA prescribes certain kinds of models to be used, how those models may be prepared and the relationships of the different kinds of models. Using the existing Cougaar architecture, the level of application composition is elevated from individual components to domain level model specifications in order to generate software artifacts. The software artifacts generation is based on a metamodel. Each component maps to a UML structured component which is then converted into multiple artifacts: Cougaar/Java code, documentation, and test cases.

Distributed parameter modeling to prevent charge cancellation for discrete thickness piezoelectric energy harvester

NASA Astrophysics Data System (ADS)

Krishnasamy, M.; Qian, Feng; Zuo, Lei; Lenka, T. R.

2018-03-01

The charge cancellation due to the change of strain along single continuous piezoelectric layer can remarkably affect the performance of a cantilever based harvester. In this paper, analytical models using distributed parameters are developed with some extent of averting the charge cancellation in cantilever piezoelectric transducer where the piezoelectric layers are segmented at strain nodes of concerned vibration mode. The electrode of piezoelectric segments are parallelly connected with a single external resistive load in the 1st model (Model 1). While each bimorph piezoelectric layers are connected in parallel to a resistor to form an independent circuit in the 2nd model (Model 2). The analytical expressions of the closed-form electromechanical coupling responses in frequency domain under harmonic base excitation are derived based on the Euler-Bernoulli beam assumption for both models. The developed analytical models are validated by COMSOL and experimental results. The results demonstrate that the energy harvesting performance of the developed segmented piezoelectric layer models is better than the traditional model of continuous piezoelectric layer.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Monopoly models with time-varying demand function

NASA Astrophysics Data System (ADS)

Cavalli, Fausto; Naimzada, Ahmad

2018-05-01

We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

Mass spectrometry for the detection of bioterrorism agents: from environmental to clinical applications.

PubMed

Duriez, Elodie; Armengaud, Jean; Fenaille, François; Ezan, Eric

2016-03-01

In the current context of international conflicts and localized terrorist actions, there is unfortunately a permanent threat of attacks with unconventional warfare agents. Among these, biological agents such as toxins, microorganisms, and viruses deserve particular attention owing to their ease of production and dissemination. Mass spectrometry (MS)-based techniques for the detection and quantification of biological agents have a decisive role to play for countermeasures in a scenario of biological attacks. The application of MS to every field of both organic and macromolecular species has in recent years been revolutionized by the development of soft ionization techniques (MALDI and ESI), and by the continuous development of MS technologies (high resolution, accurate mass HR/AM instruments, novel analyzers, hybrid configurations). New possibilities have emerged for exquisite specific and sensitive detection of biological warfare agents. MS-based strategies for clinical application can now address a wide range of analytical questions mainly including issues related to the complexity of biological samples and their available volume. Multiplexed toxin detection, discovery of new markers through omics approaches, and identification of untargeted microbiological or of novel molecular targets are examples of applications. In this paper, we will present these technological advances along with the novel perspectives offered by omics approaches to clinical detection and follow-up. Copyright © 2016 John Wiley & Sons, Ltd.

Safe motion planning for mobile agents: A model of reactive planning for multiple mobile agents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fujimura, Kikuo.

1990-01-01

The problem of motion planning for multiple mobile agents is studied. Each planning agent independently plans its own action based on its map which contains a limited information about the environment. In an environment where more than one mobile agent interacts, the motions of the robots are uncertain and dynamic. A model for reactive agents is described and simulation results are presented to show their behavior patterns. 18 refs., 2 figs.

An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

NASA Technical Reports Server (NTRS)

Provance, Mike; Collins, Andrew; Carayannis, Elias

2012-01-01

There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

Automated Predictive Big Data Analytics Using Ontology Based Semantics.

PubMed

Nural, Mustafa V; Cotterell, Michael E; Peng, Hao; Xie, Rui; Ma, Ping; Miller, John A

2015-10-01

Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not always be readily available. In this paper, we propose to use semantic technology to assist data analysts and data scientists in selecting appropriate modeling techniques and building specific models as well as the rationale for the techniques and models selected. To formally describe the modeling techniques, models and results, we developed the Analytics Ontology that supports inferencing for semi-automated model selection. The SCALATION framework, which currently supports over thirty modeling techniques for predictive big data analytics is used as a testbed for evaluating the use of semantic technology.

Automated Predictive Big Data Analytics Using Ontology Based Semantics

PubMed Central

Nural, Mustafa V.; Cotterell, Michael E.; Peng, Hao; Xie, Rui; Ma, Ping; Miller, John A.

2017-01-01

Predictive analytics in the big data era is taking on an ever increasingly important role. Issues related to choice on modeling technique, estimation procedure (or algorithm) and efficient execution can present significant challenges. For example, selection of appropriate and optimal models for big data analytics often requires careful investigation and considerable expertise which might not always be readily available. In this paper, we propose to use semantic technology to assist data analysts and data scientists in selecting appropriate modeling techniques and building specific models as well as the rationale for the techniques and models selected. To formally describe the modeling techniques, models and results, we developed the Analytics Ontology that supports inferencing for semi-automated model selection. The SCALATION framework, which currently supports over thirty modeling techniques for predictive big data analytics is used as a testbed for evaluating the use of semantic technology. PMID:29657954

A Primer for Agent-Based Simulation and Modeling in Transportation Applications

DOT National Transportation Integrated Search

2013-11-01

Agent-based modeling and simulation (ABMS) methods have been applied in a spectrum of research domains. This primer focuses on ABMS in the transportation interdisciplinary domain, describes the basic concepts of ABMS and the recent progress of ABMS i...

Interacting with an artificial partner: modeling the role of emotional aspects.

PubMed

Cattinelli, Isabella; Goldwurm, Massimiliano; Borghese, N Alberto

2008-12-01

In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated agents. Based on the agent's personality, attitude, and nature, and on the emotional inputs it receives, the model will determine the next emotional state displayed by the agent itself. The probabilistic and time-varying nature of the model yields rich and dynamic interactions, and an autonomous adaptation to the interlocutor. In addition, a reinforcement learning technique is applied to have one agent drive its partner's behavior toward desired states. The model may also be used as a tool for behavior analysis, by extracting high probability patterns of interaction and by resorting to the ergodic properties of Markov chains.

Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity

NASA Astrophysics Data System (ADS)

Manfredi, S.; Di Tucci, E.; Latora, V.

2018-02-01

Multilayer networks describe well many real interconnected communication and transportation systems, ranging from computer networks to multimodal mobility infrastructures. Here, we introduce a model in which the nodes have a limited capacity of storing and processing the agents moving over a multilayer network, and their congestions trigger temporary faults which, in turn, dynamically affect the routing of agents seeking for uncongested paths. The study of the network performance under different layer velocities and node maximum capacities reveals the existence of delicate trade-offs between the number of served agents and their time to travel to destination. We provide analytical estimates of the optimal buffer size at which the travel time is minimum and of its dependence on the velocity and number of links at the different layers. Phenomena reminiscent of the slower is faster effect and of the Braess' paradox are observed in our dynamical multilayer setup.

Mobility and Congestion in Dynamical Multilayer Networks with Finite Storage Capacity.

PubMed

Manfredi, S; Di Tucci, E; Latora, V

2018-02-09

Multilayer networks describe well many real interconnected communication and transportation systems, ranging from computer networks to multimodal mobility infrastructures. Here, we introduce a model in which the nodes have a limited capacity of storing and processing the agents moving over a multilayer network, and their congestions trigger temporary faults which, in turn, dynamically affect the routing of agents seeking for uncongested paths. The study of the network performance under different layer velocities and node maximum capacities reveals the existence of delicate trade-offs between the number of served agents and their time to travel to destination. We provide analytical estimates of the optimal buffer size at which the travel time is minimum and of its dependence on the velocity and number of links at the different layers. Phenomena reminiscent of the slower is faster effect and of the Braess' paradox are observed in our dynamical multilayer setup.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

Layer-switching cost and optimality in information spreading on multiplex networks

PubMed Central

Min, Byungjoon; Gwak, Sang-Hwan; Lee, Nanoom; Goh, K. -I.

2016-01-01

We study a model of information spreading on multiplex networks, in which agents interact through multiple interaction channels (layers), say online vs. offline communication layers, subject to layer-switching cost for transmissions across different interaction layers. The model is characterized by the layer-wise path-dependent transmissibility over a contact, that is dynamically determined dependently on both incoming and outgoing transmission layers. We formulate an analytical framework to deal with such path-dependent transmissibility and demonstrate the nontrivial interplay between the multiplexity and spreading dynamics, including optimality. It is shown that the epidemic threshold and prevalence respond to the layer-switching cost non-monotonically and that the optimal conditions can change in abrupt non-analytic ways, depending also on the densities of network layers and the type of seed infections. Our results elucidate the essential role of multiplexity that its explicit consideration should be crucial for realistic modeling and prediction of spreading phenomena on multiplex social networks in an era of ever-diversifying social interaction layers. PMID:26887527

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

PubMed

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

Adapting Price Predictions in TAC SCM

NASA Astrophysics Data System (ADS)

Pardoe, David; Stone, Peter

In agent-based markets, adapting to the behavior of other agents is often necessary for success. When it is not possible to directly model individual competitors, an agent may instead model and adapt to the market conditions that result from competitor behavior. Such an agent could still benefit from reasoning about specific competitor strategies by considering how various combinations of these strategies would impact the conditions being modeled. We present an application of such an approach to a specific prediction problem faced by the agent TacTex-06 in the Trading Agent Competition's Supply Chain Management scenario (TAC SCM).

Modeling persistence of motion in a crowded environment: The diffusive limit of excluding velocity-jump processes

NASA Astrophysics Data System (ADS)

Gavagnin, Enrico; Yates, Christian A.

2018-03-01

Persistence of motion is the tendency of an object to maintain motion in a direction for short time scales without necessarily being biased in any direction in the long term. One of the most appropriate mathematical tools to study this behavior is an agent-based velocity-jump process. In the absence of agent-agent interaction, the mean-field continuum limit of the agent-based model (ABM) gives rise to the well known hyperbolic telegraph equation. When agent-agent interaction is included in the ABM, a strictly advective system of partial differential equations (PDEs) can be derived at the population level. However, no diffusive limit of the ABM has been obtained from such a model. Connecting the microscopic behavior of the ABM to a diffusive macroscopic description is desirable, since it allows the exploration of a wider range of scenarios and establishes a direct connection with commonly used statistical tools of movement analysis. In order to connect the ABM at the population level to a diffusive PDE at the population level, we consider a generalization of the agent-based velocity-jump process on a two-dimensional lattice with three forms of agent interaction. This generalization allows us to take a diffusive limit and obtain a faithful population-level description. We investigate the properties of the model at both the individual and population levels and we elucidate some of the models' key characteristic features. In particular, we show an intrinsic anisotropy inherent to the models and we find evidence of a spontaneous form of aggregation at both the micro- and macroscales.

Chemoviscosity modeling for thermosetting resins - I

NASA Technical Reports Server (NTRS)

Hou, T. H.

1984-01-01

A new analytical model for chemoviscosity variation during cure of thermosetting resins was developed. This model is derived by modifying the widely used WLF (Williams-Landel-Ferry) Theory in polymer rheology. Major assumptions involved are that the rate of reaction is diffusion controlled and is linearly inversely proportional to the viscosity of the medium over the entire cure cycle. The resultant first order nonlinear differential equation is solved numerically, and the model predictions compare favorably with experimental data of EPON 828/Agent U obtained on a Rheometrics System 4 Rheometer. The model describes chemoviscosity up to a range of six orders of magnitude under isothermal curing conditions. The extremely non-linear chemoviscosity profile for a dynamic heating cure cycle is predicted as well. The model is also shown to predict changes of glass transition temperature for the thermosetting resin during cure. The physical significance of this prediction is unclear at the present time, however, and further research is required. From the chemoviscosity simulation point of view, the technique of establishing an analytical model as described here is easily applied to any thermosetting resin. The model thus obtained is used in real-time process controls for fabricating composite materials.

Minority game and anomalies in financial markets

NASA Astrophysics Data System (ADS)

Liu, Xinghua; Liang, Xiaobei; Tang, Bingyong

2004-02-01

The minority game (MG), which is intrinsically associated with financial markets, is an agent-based model of a competing population with limited resources. We find that the fluctuation features of MG in crowded region are more similar to real market than that of in perfect cooperation region. So we propose and study a modified model based on the MG in which agents accumulate virtual points for their strategies from the last H steps instead of from the beginning of the game. The results of numerical simulations on our new model show that agents will be more intelligent, and the types of features of fluctuations are the same in real-world market. We also give a numerical explanation of the high adaptability of agents in new model.

Efficient Agent-Based Models for Non-Genomic Evolution

NASA Technical Reports Server (NTRS)

Gupta, Nachi; Agogino, Adrian; Tumer, Kagan

2006-01-01

Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science involving early evolutionary structures and the origins of life. Unfortunately traditional non-multi-agent methods either require oversimplified models or are slow to converge to adequate solutions. This paper shows how to address these deficiencies by modeling the protein aggregations through a utility based multi-agent system. In this method each agent controls the properties of a set of proteins assigned to that agent. Some of these properties determine the dynamics of the system, such as the ability for some proteins to join or split other proteins, while additional properties determine the aggregation s fitness as a viable primitive cell. We show that over a wide range of starting conditions, there are mechanisins that allow protein aggregations to achieve high values of overall fitness. In addition through the use of agent-specific utilities that remain aligned with the overall global utility, we are able to reach these conclusions with 50 times fewer learning steps.

Dual Rationality and Deliberative Agents

NASA Astrophysics Data System (ADS)

Debenham, John; Sierra, Carles

Human agents deliberate using models based on reason for only a minute proportion of the decisions that they make. In stark contrast, the deliberation of artificial agents is heavily dominated by formal models based on reason such as game theory, decision theory and logic—despite that fact that formal reasoning will not necessarily lead to superior real-world decisions. Further the Nobel Laureate Friedrich Hayek warns us of the ‘fatal conceit’ in controlling deliberative systems using models based on reason as the particular model chosen will then shape the system’s future and either impede, or eventually destroy, the subtle evolutionary processes that are an integral part of human systems and institutions, and are crucial to their evolution and long-term survival. We describe an architecture for artificial agents that is founded on Hayek’s two rationalities and supports the two forms of deliberation used by mankind.

Integration of gas chromatography mass spectrometry methods for differentiating ricin preparation methods.

PubMed

Wunschel, David S; Melville, Angela M; Ehrhardt, Christopher J; Colburn, Heather A; Victry, Kristin D; Antolick, Kathryn C; Wahl, Jon H; Wahl, Karen L

2012-05-07

The investigation of crimes involving chemical or biological agents is infrequent, but presents unique analytical challenges. The protein toxin ricin is encountered more frequently than other agents and is found in the seeds of Ricinus communis, commonly known as the castor plant. Typically, the toxin is extracted from castor seeds utilizing a variety of different recipes that result in varying purity of the toxin. Moreover, these various purification steps can also leave or differentially remove a variety of exogenous and endogenous residual components with the toxin that may indicate the type and number of purification steps involved. We have applied three gas chromatography-mass spectrometry (GC-MS) based analytical methods to measure the variation in seed carbohydrates and castor oil ricinoleic acid, as well as the presence of solvents used for purification. These methods were applied to the same samples prepared using four previously identified toxin preparation methods, starting from four varieties of castor seeds. The individual data sets for seed carbohydrate profiles, ricinoleic acid, or acetone amount each provided information capable of differentiating different types of toxin preparations across seed types. However, the integration of the data sets using multivariate factor analysis provided a clear distinction of all samples based on the preparation method, independent of the seed source. In particular, the abundance of mannose, arabinose, fucose, ricinoleic acid, and acetone were shown to be important differentiating factors. These complementary tools provide a more confident determination of the method of toxin preparation than would be possible using a single analytical method.

Assessment of sample preservation techniques for pharmaceuticals, personal care products, and steroids in surface and drinking water.

PubMed

Vanderford, Brett J; Mawhinney, Douglas B; Trenholm, Rebecca A; Zeigler-Holady, Janie C; Snyder, Shane A

2011-02-01

Proper collection and preservation techniques are necessary to ensure sample integrity and maintain the stability of analytes until analysis. Data from improperly collected and preserved samples could lead to faulty conclusions and misinterpretation of the occurrence and fate of the compounds being studied. Because contaminants of emerging concern, such as pharmaceuticals and personal care products (PPCPs) and steroids, generally occur in surface and drinking water at ng/L levels, these compounds in particular require such protocols to accurately assess their concentrations. In this study, sample bottle types, residual oxidant quenching agents, preservation agents, and hold times were assessed for 21 PPCPs and steroids in surface water and finished drinking water. Amber glass bottles were found to have the least effect on target analyte concentrations, while high-density polyethylene bottles had the most impact. Ascorbic acid, sodium thiosulfate, and sodium sulfite were determined to be acceptable quenching agents and preservation with sodium azide at 4 °C led to the stability of the most target compounds. A combination of amber glass bottles, ascorbic acid, and sodium azide preserved analyte concentrations for 28 days in the tested matrices when held at 4 °C. Samples without a preservation agent were determined to be stable for all but two of the analytes when stored in amber glass bottles at 4 °C for 72 h. Results suggest that if improper protocols are utilized, reported concentrations of target PPCPs and steroids may be inaccurate.

Anabolic agents: recent strategies for their detection and protection from inadvertent doping

PubMed Central

Geyer, Hans; Schänzer, Wilhelm; Thevis, Mario

2014-01-01

According to the World Anti-Doping Agency (WADA) Prohibited List, anabolic agents consist of exogenous anabolic androgenic steroids (AAS), endogenous AAS and other anabolic agents such as clenbuterol and selective androgen receptor modulators (SARMs). Currently employed strategies for their improved detection include the prolongation of the detection windows for exogenous AAS, non-targeted and indirect analytical approaches for the detection of modified steroids (designer steroids), the athlete’s biological passport and isotope ratio mass spectrometry for the detection of the misuse of endogenous AAS, as well as preventive doping research for the detection of SARMs. The recent use of these strategies led to 4–80-fold increases of adverse analytical findings for exogenous AAS, to the detection of the misuse of new designer steroids, to adverse analytical findings of different endogenous AAS and to the first adverse analytical findings of SARMs. The strategies of the antidoping research are not only focused on the development of methods to catch the cheating athlete but also to protect the clean athlete from inadvertent doping. Within the past few years several sources of inadvertent doping with anabolic agents have been identified. Among these are nutritional supplements adulterated with AAS, meat products contaminated with clenbuterol, mycotoxin (zearalenone) contamination leading to zeranol findings, and natural products containing endogenous AAS. The protection strategy consists of further investigations in case of reasonable suspicion of inadvertent doping, publication of the results, education of athletes and development of methods to differentiate between intentional and unintentional doping. PMID:24632537

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

Can agent based models effectively reduce fisheries management implementation uncertainty?

NASA Astrophysics Data System (ADS)

Drexler, M.

2016-02-01

Uncertainty is an inherent feature of fisheries management. Implementation uncertainty remains a challenge to quantify often due to unintended responses of users to management interventions. This problem will continue to plague both single species and ecosystem based fisheries management advice unless the mechanisms driving these behaviors are properly understood. Equilibrium models, where each actor in the system is treated as uniform and predictable, are not well suited to forecast the unintended behaviors of individual fishers. Alternatively, agent based models (AMBs) can simulate the behaviors of each individual actor driven by differing incentives and constraints. This study evaluated the feasibility of using AMBs to capture macro scale behaviors of the US West Coast Groundfish fleet. Agent behavior was specified at the vessel level. Agents made daily fishing decisions using knowledge of their own cost structure, catch history, and the histories of catch and quota markets. By adding only a relatively small number of incentives, the model was able to reproduce highly realistic macro patterns of expected outcomes in response to management policies (catch restrictions, MPAs, ITQs) while preserving vessel heterogeneity. These simulations indicate that agent based modeling approaches hold much promise for simulating fisher behaviors and reducing implementation uncertainty. Additional processes affecting behavior, informed by surveys, are continually being added to the fisher behavior model. Further coupling of the fisher behavior model to a spatial ecosystem model will provide a fully integrated social, ecological, and economic model capable of performing management strategy evaluations to properly consider implementation uncertainty in fisheries management.

A simple analytical aerodynamic model of Langley Winged-Cone Aerospace Plane concept

NASA Technical Reports Server (NTRS)

Pamadi, Bandu N.

1994-01-01

A simple three DOF analytical aerodynamic model of the Langley Winged-Coned Aerospace Plane concept is presented in a form suitable for simulation, trajectory optimization, and guidance and control studies. The analytical model is especially suitable for methods based on variational calculus. Analytical expressions are presented for lift, drag, and pitching moment coefficients from subsonic to hypersonic Mach numbers and angles of attack up to +/- 20 deg. This analytical model has break points at Mach numbers of 1.0, 1.4, 4.0, and 6.0. Across these Mach number break points, the lift, drag, and pitching moment coefficients are made continuous but their derivatives are not. There are no break points in angle of attack. The effect of control surface deflection is not considered. The present analytical model compares well with the APAS calculations and wind tunnel test data for most angles of attack and Mach numbers.

Systems, methods and apparatus for modeling, specifying and deploying policies in autonomous and autonomic systems using agent-oriented software engineering

NASA Technical Reports Server (NTRS)

Sterritt, Roy (Inventor); Hinchey, Michael G. (Inventor); Penn, Joaquin (Inventor)

2011-01-01

Systems, methods and apparatus are provided through which in some embodiments, an agent-oriented specification modeled with MaCMAS, is analyzed, flaws in the agent-oriented specification modeled with MaCMAS are corrected, and an implementation is derived from the corrected agent-oriented specification. Described herein are systems, method and apparatus that produce fully (mathematically) tractable development of agent-oriented specification(s) modeled with methodology fragment for analyzing complex multiagent systems (MaCMAS) and policies for autonomic systems from requirements through to code generation. The systems, method and apparatus described herein are illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming systems, method and apparatus described herein may provide faster, higher quality development and maintenance of autonomic systems based on user formulation of policies.

When push comes to shove: Exclusion processes with nonlocal consequences

NASA Astrophysics Data System (ADS)

Almet, Axel A.; Pan, Michael; Hughes, Barry D.; Landman, Kerry A.

2015-11-01

Stochastic agent-based models are useful for modelling collective movement of biological cells. Lattice-based random walk models of interacting agents where each site can be occupied by at most one agent are called simple exclusion processes. An alternative motility mechanism to simple exclusion is formulated, in which agents are granted more freedom to move under the compromise that interactions are no longer necessarily local. This mechanism is termed shoving. A nonlinear diffusion equation is derived for a single population of shoving agents using mean-field continuum approximations. A continuum model is also derived for a multispecies problem with interacting subpopulations, which either obey the shoving rules or the simple exclusion rules. Numerical solutions of the derived partial differential equations compare well with averaged simulation results for both the single species and multispecies processes in two dimensions, while some issues arise in one dimension for the multispecies case.

A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: from cognitive maps to agent-based models.

PubMed

Elsawah, Sondoss; Guillaume, Joseph H A; Filatova, Tatiana; Rook, Josefine; Jakeman, Anthony J

2015-03-15

This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical and analytical modeling of the end-loaded split (ELS) test specimens made of multi-directional coupled composite laminates

NASA Astrophysics Data System (ADS)

Samborski, Sylwester; Valvo, Paolo S.

2018-01-01

The paper deals with the numerical and analytical modelling of the end-loaded split test for multi-directional laminates affected by the typical elastic couplings. Numerical analysis of three-dimensional finite element models was performed with the Abaqus software exploiting the virtual crack closure technique (VCCT). The results show possible asymmetries in the widthwise deflections of the specimen, as well as in the strain energy release rate (SERR) distributions along the delamination front. Analytical modelling based on a beam-theory approach was also conducted in simpler cases, where only bending-extension coupling is present, but no out-of-plane effects. The analytical results matched the numerical ones, thus demonstrating that the analytical models are feasible for test design and experimental data reduction.

Quantitative Detection of Nucleoside Analogues by Multi-enzyme Biosensors using Time-Resolved Kinetic Measurements.

PubMed

Muthu, Pravin; Lutz, Stefan

2016-04-05

Fast, simple and cost-effective methods for detecting and quantifying pharmaceutical agents in patients are highly sought after to replace equipment and labor-intensive analytical procedures. The development of new diagnostic technology including portable detection devices also enables point-of-care by non-specialists in resource-limited environments. We have focused on the detection and dose monitoring of nucleoside analogues used in viral and cancer therapies. Using deoxyribonucleoside kinases (dNKs) as biosensors, our chemometric model compares observed time-resolved kinetics of unknown analytes to known substrate interactions across multiple enzymes. The resulting dataset can simultaneously identify and quantify multiple nucleosides and nucleoside analogues in complex sample mixtures. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy.

PubMed

Day, Theodore Eugene; Ravi, Nathan; Xian, Hong; Brugh, Ann

2013-01-01

Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted. Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort. The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001). Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.

Cooperation in group-structured populations with two layers of interactions

PubMed Central

Zhang, Yanling; Fu, Feng; Chen, Xiaojie; Xie, Guangming; Wang, Long

2015-01-01

Recently there has been a growing interest in studying multiplex networks where individuals are structured in multiple network layers. Previous agent-based simulations of games on multiplex networks reveal rich dynamics arising from interdependency of interactions along each network layer, yet there is little known about analytical conditions for cooperation to evolve thereof. Here we aim to tackle this issue by calculating the evolutionary dynamics of cooperation in group-structured populations with two layers of interactions. In our model, an individual is engaged in two layers of group interactions simultaneously and uses unrelated strategies across layers. Evolutionary competition of individuals is determined by the total payoffs accrued from two layers of interactions. We also consider migration which allows individuals to move to a new group within each layer. An approach combining the coalescence theory with the theory of random walks is established to overcome the analytical difficulty upon local migration. We obtain the exact results for all “isotropic” migration patterns, particularly for migration tuned with varying ranges. When the two layers use one game, the optimal migration ranges are proved identical across layers and become smaller as the migration probability grows. PMID:26632251

Robust reinforcement learning.

PubMed

Morimoto, Jun; Doya, Kenji

2005-02-01

This letter proposes a new reinforcement learning (RL) paradigm that explicitly takes into account input disturbance as well as modeling errors. The use of environmental models in RL is quite popular for both offline learning using simulations and for online action planning. However, the difference between the model and the real environment can lead to unpredictable, and often unwanted, results. Based on the theory of H(infinity) control, we consider a differential game in which a "disturbing" agent tries to make the worst possible disturbance while a "control" agent tries to make the best control input. The problem is formulated as finding a min-max solution of a value function that takes into account the amount of the reward and the norm of the disturbance. We derive online learning algorithms for estimating the value function and for calculating the worst disturbance and the best control in reference to the value function. We tested the paradigm, which we call robust reinforcement learning (RRL), on the control task of an inverted pendulum. In the linear domain, the policy and the value function learned by online algorithms coincided with those derived analytically by the linear H(infinity) control theory. For a fully nonlinear swing-up task, RRL achieved robust performance with changes in the pendulum weight and friction, while a standard reinforcement learning algorithm could not deal with these changes. We also applied RRL to the cart-pole swing-up task, and a robust swing-up policy was acquired.

Equilibria, information and frustration in heterogeneous network games with conflicting preferences

NASA Astrophysics Data System (ADS)

Mazzoli, M.; Sánchez, A.

2017-11-01

Interactions between people are the basis on which the structure of our society arises as a complex system and, at the same time, are the starting point of any physical description of it. In the last few years, much theoretical research has addressed this issue by combining the physics of complex networks with a description of interactions in terms of evolutionary game theory. We here take this research a step further by introducing a most salient societal factor such as the individuals’ preferences, a characteristic that is key to understanding much of the social phenomenology these days. We consider a heterogeneous, agent-based model in which agents interact strategically with their neighbors, but their preferences and payoffs for the possible actions differ. We study how such a heterogeneous network behaves under evolutionary dynamics and different strategic interactions, namely coordination games and best shot games. With this model we study the emergence of the equilibria predicted analytically in random graphs under best response dynamics, and we extend this test to unexplored contexts like proportional imitation and scale free networks. We show that some theoretically predicted equilibria do not arise in simulations with incomplete information, and we demonstrate the importance of the graph topology and the payoff function parameters for some games. Finally, we discuss our results with the available experimental evidence on coordination games, showing that our model agrees better with the experiment than standard economic theories, and draw hints as to how to maximize social efficiency in situations of conflicting preferences.

Laser backscattering analytical model of Doppler power spectra about rotating convex quadric bodies of revolution

NASA Astrophysics Data System (ADS)

Gong, YanJun; Wu, ZhenSen; Wang, MingJun; Cao, YunHua

2010-01-01

We propose an analytical model of Doppler power spectra in backscatter from arbitrary rough convex quadric bodies of revolution (whose lateral surface is a quadric) rotating around axes. In the global Cartesian coordinate system, the analytical model deduced is suitable for general convex quadric body of revolution. Based on this analytical model, the Doppler power spectra of cones, cylinders, paraboloids of revolution, and sphere-cones combination are proposed. We analyze numerically the influence of geometric parameters, aspect angle, wavelength and reflectance of rough surface of the objects on the broadened spectra because of the Doppler effect. This analytical solution may contribute to laser Doppler velocimetry, and remote sensing of ballistic missile that spin.

LARC-1: a Los Alamos release calculation program for fission product transport in HTGRs during the LOFC accident

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carruthers, L.M.; Lee, C.E.

1976-10-01

The theoretical and numerical data base development of the LARC-1 code is described. Four analytical models of fission product release from an HTGR core during the loss of forced circulation accident are developed. Effects of diffusion, adsorption and evaporation of the metallics and precursors are neglected in this first LARC model. Comparison of the analytic models indicates that the constant release-renormalized model is adequate to describe the processes involved. The numerical data base for release constants, temperature modeling, fission product release rates, coated fuel particle failure fraction and aged coated fuel particle failure fractions is discussed. Analytic fits and graphicmore » displays for these data are given for the Ft. St. Vrain and GASSAR models.« less

Introductory Chemistry: A Molar Relaxivity Experiment in the High School Classroom.

PubMed

Dawsey, Anna C; Hathaway, Kathryn L; Kim, Susie; Williams, Travis J

2013-07-09

Dotarem and Magnevist, two clinically available magnetic resonance imaging (MRI) contrast agents, were assessed in a high school science classroom with respect to which is the better contrast agent. Magnevist, the more efficacious contrast agent, has negative side effects because its gadolinium center can escape from its ligand. However, Dotarem, though a less efficacious contrast agent, is a safer drug choice. After the experiment, students are confronted with the FDA warning on Magnevist, which enabled a discussion of drug efficacy versus safety. We describe a laboratory experiment in which NMR spin lattice relaxation rate measurements are used to quantify the relaxivities of the active ingredients of Dotarem and Magnevist. The spin lattice relaxation rate gives the average amount of time it takes the excited nucleus to relax back to the original state. Students learn by constructing molar relaxivity curves based on inversion recovery data sets that Magnevist is more relaxive than Dotarem. This experiment is suitable for any analytical chemistry laboratory with access to NMR.

Dramatic Expression in Opera, and Its Implications for Conversational Agents. Chapter 7

NASA Technical Reports Server (NTRS)

Johnson, W. Lewis

2007-01-01

This article has discussed principles, techniques, and methods of dramatic portrayal in opera, and their application to the development of embodied conversational agents. Investigations such as this complement studies of natural human behavior, and offer insights as to how to make such behavior understandable and interesting when adapted for use by embodied conversational agents. However, one should use caution in applying such lessons. The unique characteristics of computer-based media are still being identified and explored. In any case, one must always be careful about applying principles blindly to any artistic form. Such principles are post-hoc analysis of the intuitive skill of great artists; this was as true in Aristotle's day as it is today. We should not let structural principles stand in the way of injecting creativity into the design of ECAs. Opera at its best possesses an element of magic that is difficult to describe, much less analytically reconstruct. We can only hope to achieve a similar result with conversational agents.

Research on bathymetry estimation by Worldview-2 based with the semi-analytical model

NASA Astrophysics Data System (ADS)

Sheng, L.; Bai, J.; Zhou, G.-W.; Zhao, Y.; Li, Y.-C.

2015-04-01

South Sea Islands of China are far away from the mainland, the reefs takes more than 95% of south sea, and most reefs scatter over interested dispute sensitive area. Thus, the methods of obtaining the reefs bathymetry accurately are urgent to be developed. Common used method, including sonar, airborne laser and remote sensing estimation, are limited by the long distance, large area and sensitive location. Remote sensing data provides an effective way for bathymetry estimation without touching over large area, by the relationship between spectrum information and bathymetry. Aimed at the water quality of the south sea of China, our paper develops a bathymetry estimation method without measured water depth. Firstly the semi-analytical optimization model of the theoretical interpretation models has been studied based on the genetic algorithm to optimize the model. Meanwhile, OpenMP parallel computing algorithm has been introduced to greatly increase the speed of the semi-analytical optimization model. One island of south sea in China is selected as our study area, the measured water depth are used to evaluate the accuracy of bathymetry estimation from Worldview-2 multispectral images. The results show that: the semi-analytical optimization model based on genetic algorithm has good results in our study area;the accuracy of estimated bathymetry in the 0-20 meters shallow water area is accepted.Semi-analytical optimization model based on genetic algorithm solves the problem of the bathymetry estimation without water depth measurement. Generally, our paper provides a new bathymetry estimation method for the sensitive reefs far away from mainland.

Propagation of Bayesian Belief for Near-Real Time Statistical Assessment of Geosynchronous Satellite Status Based on Non-Resolved Photometry Data

DTIC Science & Technology

2014-09-01

of the BRDF for the Body and Panel. In order to provide a continuously updated baseline, the Photometry Model application is performed using a...brightness to its predicted brightness. The brightness predictions can be obtained using any analytical model chosen by the user. The inference for a...the analytical model as possible; and to mitigate the effect of bias that could be introduced by the choice of analytical model . It considers that a

Adding ecosystem function to agent-based land use models

USDA-ARS?s Scientific Manuscript database

The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeoche...

Determination of glycols in air: development of sampling and analytical methodology and application to theatrical smokes.

PubMed

Pendergrass, S M

1999-01-01

Glycol-based fluids are used in the production of theatrical smokes in theaters, concerts, and other stage productions. The fluids are heated and dispersed in aerosol form to create the effect of a smoke, mist, or fog. There have been reports of adverse health effects such as respiratory irritation, chest tightness, shortness of breath, asthma, and skin rashes. Previous attempts to collect and quantify the aerosolized glycols used in fogging agents have been plagued by inconsistent results, both in the efficiency of collection and in the chromatographic analysis of the glycol components. The development of improved sampling and analytical methodology for aerosolized glycols was required to assess workplace exposures more effectively. An Occupational Safety and Health Administration versatile sampler tube was selected for the collection of ethylene glycol, propylene glycol, 1,3-butylene glycol, diethylene glycol, triethylene glycol, and tetraethylene glycol aerosols. Analytical methodology for the separation, identification, and quantitation of the six glycols using gas chromatography/flame ionization detection is described. Limits of detection of the glycol analytes ranged from 7 to 16 micrograms/sample. Desorption efficiencies for all glycol compounds were determined over the range of study and averaged greater than 90%. Storage stability results were acceptable after 28 days for all analytes except ethylene glycol, which was stable at ambient temperature for 14 days. Based on the results of this study, the new glycol method was published in the NIOSH Manual of Analytical Methods.

Transition to parenthood: the role of social interaction and endogenous networks.

PubMed

Diaz, Belinda Aparicio; Fent, Thomas; Prskawetz, Alexia; Bernardi, Laura

2011-05-01

Empirical studies indicate that the transition to parenthood is influenced by an individual's peer group. To study the mechanisms creating interdependencies across individuals' transition to parenthood and its timing, we apply an agent-based simulation model. We build a one-sex model and provide agents with three different characteristics: age, intended education, and parity. Agents endogenously form their network based on social closeness. Network members may then influence the agents' transition to higher parity levels. Our numerical simulations indicate that accounting for social interactions can explain the shift of first-birth probabilities in Austria during the period 1984 to 2004. Moreover, we apply our model to forecast age-specific fertility rates up to 2016.

Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions.

PubMed

Sanchez-Anguix, Victor; Julian, Vicente; Botti, Vicente; García-Fornes, Ana

2012-06-01

In this article, an agent-based negotiation model for negotiation teams that negotiate a deal with an opponent is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round. This work analyzes how unanimous decisions are taken within the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.

An Application of Artificial Intelligence to the Implementation of Electronic Commerce

NASA Astrophysics Data System (ADS)

Srivastava, Anoop Kumar

In this paper, we present an application of Artificial Intelligence (AI) to the implementation of Electronic Commerce. We provide a multi autonomous agent based framework. Our agent based architecture leads to flexible design of a spectrum of multiagent system (MAS) by distributing computation and by providing a unified interface to data and programs. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, structure of Electronic Marketplace, an ontology, the agent model, and interaction pattern between agents is given. We have developed mechanisms for coordination between agents using a language, which is called Virtual Enterprise Modeling Language (VEML). VEML is a integration of Java and Knowledge Query and Manipulation Language (KQML). VEML provides application programmers with potential to globally develop different kinds of MAS based on their requirements and applications. We have implemented a multi autonomous agent based system called VE System. We demonstrate efficacy of our system by discussing experimental results and its salient features.

Fractional discrete-time consensus models for single- and double-summator dynamics

NASA Astrophysics Data System (ADS)

Wyrwas, Małgorzata; Mozyrska, Dorota; Girejko, Ewa

2018-04-01

The leader-following consensus problem of fractional-order multi-agent discrete-time systems is considered. In the systems, interactions between opinions are defined like in Krause and Cucker-Smale models but the memory is included by taking the fractional-order discrete-time operator on the left-hand side of the nonlinear systems. In this paper, we investigate fractional-order models of opinions for the single- and double-summator dynamics of discrete-time by analytical methods as well as by computer simulations. The necessary and sufficient conditions for the leader-following consensus are formulated by proposing a consensus control law for tracking the virtual leader.

Universality in survivor distributions: Characterizing the winners of competitive dynamics

NASA Astrophysics Data System (ADS)

Luck, J. M.; Mehta, A.

2015-11-01

We investigate the survivor distributions of a spatially extended model of competitive dynamics in different geometries. The model consists of a deterministic dynamical system of individual agents at specified nodes, which might or might not survive the predatory dynamics: all stochasticity is brought in by the initial state. Every such initial state leads to a unique and extended pattern of survivors and nonsurvivors, which is known as an attractor of the dynamics. We show that the number of such attractors grows exponentially with system size, so that their exact characterization is limited to only very small systems. Given this, we construct an analytical approach based on inhomogeneous mean-field theory to calculate survival probabilities for arbitrary networks. This powerful (albeit approximate) approach shows how universality arises in survivor distributions via a key concept—the dynamical fugacity. Remarkably, in the large-mass limit, the survivor probability of a node becomes independent of network geometry and assumes a simple form which depends only on its mass and degree.

The Driving Forces of Cultural Complexity : Neanderthals, Modern Humans, and the Question of Population Size.

PubMed

Fogarty, Laurel; Wakano, Joe Yuichiro; Feldman, Marcus W; Aoki, Kenichi

2017-03-01

The forces driving cultural accumulation in human populations, both modern and ancient, are hotly debated. Did genetic, demographic, or cognitive features of behaviorally modern humans (as opposed to, say, early modern humans or Neanderthals) allow culture to accumulate to its current, unprecedented levels of complexity? Theoretical explanations for patterns of accumulation often invoke demographic factors such as population size or density, whereas statistical analyses of variation in cultural complexity often point to the importance of environmental factors such as food stability, in determining cultural complexity. Here we use both an analytical model and an agent-based simulation model to show that a full understanding of the emergence of behavioral modernity, and the cultural evolution that has followed, depends on understanding and untangling the complex relationships among culture, genetically determined cognitive ability, and demographic history. For example, we show that a small but growing population could have a different number of cultural traits from a shrinking population with the same absolute number of individuals in some circumstances.

Challenges and Opportunities in Analysing Students Modelling

ERIC Educational Resources Information Center

Blanco-Anaya, Paloma; Justi, Rosária; Díaz de Bustamante, Joaquín

2017-01-01

Modelling-based teaching activities have been designed and analysed from distinct theoretical perspectives. In this paper, we use one of them--the model of modelling diagram (MMD)--as an analytical tool in a regular classroom context. This paper examines the challenges that arise when the MMD is used as an analytical tool to characterise the…

Significance Testing in Confirmatory Factor Analytic Models.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Hocevar, Dennis

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…

The comparison of the use of holonic and agent-based methods in modelling of manufacturing systems

NASA Astrophysics Data System (ADS)

Foit, K.; Banaś, W.; Gwiazda, A.; Hryniewicz, P.

2017-08-01

The rapid evolution in the field of industrial automation and manufacturing is often called the 4th Industry Revolution. Worldwide availability of the internet access contributes to the competition between manufacturers, gives the opportunity for buying materials, parts and for creating the partnership networks, like cloud manufacturing, grid manufacturing (MGrid), virtual enterprises etc. The effect of the industry evolution is the need to search for new solutions in the field of manufacturing systems modelling and simulation. During the last decade researchers have developed the agent-based approach of modelling. This methodology have been taken from the computer science, but was adapted to the philosophy of industrial automation and robotization. The operation of the agent-based system depends on the simultaneous acting of different agents that may have different roles. On the other hand, there is the holon-based approach that uses the structures created by holons. It differs from the agent-based structure in some aspects, while the other ones are quite similar in both methodologies. The aim of this paper is to present the both methodologies and discuss the similarities and the differences. This may could help to select the optimal method of modelling, according to the considered problem and software resources.

CulSim: A simulator of emergence and resilience of cultural diversity

NASA Astrophysics Data System (ADS)

Ulloa, Roberto

CulSim is an agent-based computer simulation software that allows further exploration of influential and recent models of emergence of cultural groups grounded in sociological theories. CulSim provides a collection of tools to analyze resilience of cultural diversity when events affect agents, institutions or global parameters of the simulations; upon combination, events can be used to approximate historical circumstances. The software provides a graphical and text-based user interface, and so makes this agent-based modeling methodology accessible to a variety of users from different research fields.

An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

NASA Astrophysics Data System (ADS)

Hossain, Md. Tofazzal

This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

Factors Affecting Higher Order Thinking Skills of Students: A Meta-Analytic Structural Equation Modeling Study

ERIC Educational Resources Information Center

Budsankom, Prayoonsri; Sawangboon, Tatsirin; Damrongpanit, Suntorapot; Chuensirimongkol, Jariya

2015-01-01

The purpose of the research is to develop and identify the validity of factors affecting higher order thinking skills (HOTS) of students. The thinking skills can be divided into three types: analytical, critical, and creative thinking. This analysis is done by applying the meta-analytic structural equation modeling (MASEM) based on a database of…

Construction of a microscopic agent-based model for firms' dynamics

NASA Astrophysics Data System (ADS)

Iyetomi, Hiroshi; Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Kaizoji, Taisei; Soma, Wataru

2005-07-01

A workable microscopic model for firms' dynamics has been constructed. The model consists of firm agents and a bank agent dynamics of which are described by balance sheets. The size distribution of firms and the temporal evolution of the bank show critical dependence on whether or not firms use perfect information on their financial conditions to draw up next production plans.

Ion-pairing HPLC methods to determine EDTA and DTPA in small molecule and biological pharmaceutical formulations.

PubMed

Wang, George; Tomasella, Frank P

2016-06-01

Ion-pairing high-performance liquid chromatography-ultraviolet (HPLC-UV) methods were developed to determine two commonly used chelating agents, ethylenediaminetetraacetic acid (EDTA) in Abilify® (a small molecule drug with aripiprazole as the active pharmaceutical ingredient) oral solution and diethylenetriaminepentaacetic acid (DTPA) in Yervoy® (a monoclonal antibody drug with ipilimumab as the active pharmaceutical ingredient) intravenous formulation. Since the analytes, EDTA and DTPA, do not contain chromophores, transition metal ions (Cu 2+ , Fe 3+ ) which generate highly stable metallocomplexes with the chelating agents were added into the sample preparation to enhance UV detection. The use of metallocomplexes with ion-pairing chromatography provides the ability to achieve the desired sensitivity and selectivity in the development of the method. Specifically, the sample preparation involving metallocomplex formation allowed sensitive UV detection. Copper was utilized for the determination of EDTA and iron was utilized for the determination of DTPA. In the case of EDTA, a gradient mobile phase separated the components of the formulation from the analyte. In the method for DTPA, the active drug substance, ipilimumab, was eluted in the void. In addition, the optimization of the concentration of the ion-pairing reagent was discussed as a means of enhancing the retention of the aminopolycarboxylic acids (APCAs) including EDTA and DTPA and the specificity of the method. The analytical method development was designed based on the chromatographic properties of the analytes, the nature of the sample matrix and the intended purpose of the method. Validation data were presented for the two methods. Finally, both methods were successfully utilized in determining the fate of the chelates.

EPOR-Based Purification and Analysis of Erythropoietin Mimetic Peptides from Human Urine by Cys-Specific Cleavage and LC/MS/MS

NASA Astrophysics Data System (ADS)

Vogel, Matthias; Thomas, Andreas; Schänzer, Wilhelm; Thevis, Mario

2015-09-01

The development of a new class of erythropoietin mimetic agents (EMA) for treating anemic conditions has been initiated with the discovery of oligopeptides capable of dimerizing the erythropoietin (EPO) receptor and thus stimulating erythropoiesis. The most promising amino acid sequences have been mounted on various different polymeric structures or carrier molecules to obtain highly active EPO-like drugs exhibiting beneficial and desirable pharmacokinetic profiles. Concomitant with creating new therapeutic options, erythropoietin mimetic peptide (EMP)-based drug candidates represent means to artificially enhance endurance performance and necessitate coverage by sports drug testing methods. Therefore, the aim of the present study was to develop a strategy for the comprehensive detection of EMPs in doping controls, which can be used complementary to existing protocols. Three model EMPs were used to provide proof-of-concept data. Following EPO receptor-facilitated purification of target analytes from human urine, the common presence of the cysteine-flanked core structure of EMPs was exploited to generate diagnostic peptides with the aid of a nonenzymatic cleavage procedure. Sensitive detection was accomplished by targeted-SIM/data-dependent MS2 analysis. Method characterization was conducted for the EMP-based drug peginesatide concerning specificity, linearity, precision, recovery, stability, ion suppression/enhancement, and limit of detection (LOD, 0.25 ng/mL). Additionally, first data for the identification of the erythropoietin mimetic peptides EMP1 and BB68 were generated, demonstrating the multi-analyte testing capability of the presented approach.

Model for Atmospheric Propagation of Spatially Combined Laser Beams

DTIC Science & Technology

2016-09-01

thesis modeling tools is discussed. In Chapter 6, the thesis validated the model with analytical computations and simulations result from...using propagation model . Based on both the analytical computation and WaveTrain results, the diraction e ects simulated in the propagation model are...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MODEL FOR ATMOSPHERIC PROPAGATION OF SPATIALLY COMBINED LASER BEAMS by Kum Leong Lee

Quantitative detection of pathogens in centrifugal microfluidic disks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koh, Chung-Yan; Schaff, Ulrich Y.; Sommer, Gregory Jon

A system and methods for detection of a nucleic acid including forming a plurality of nucleic acid detection complexes are described, each of the complexes including a nucleic acid analyte, a detection agent and a functionalized probe. The method further including binding the nucleic acid detection complexes to a plurality of functionalized particles in a fluid sample and separating the functionalized particles having the nucleic acid detection complexes bound thereto from the fluid sample using a density media. The nucleic acid analyte is detected by detecting the detection agent.

Mitigation of short-term disturbance negative impacts in the agent-based model of a production companies network

NASA Astrophysics Data System (ADS)

Shevchuk, G. K.; Berg, D. B.; Zvereva, O. M.; Medvedeva, M. A.

2017-11-01

This article is devoted to the study of a supply chain disturbance impact on manufacturing volumes in a production system network. Each network agent's product can be used as a resource by other system agents (manufacturers). A supply chain disturbance can lead to operating cease of the entire network. Authors suggest using of short-term partial resources reservation to mitigate negative consequences of such disturbances. An agent-based model with a reservation algorithm compatible with strategies for resource procurement in terms of financial constraints was engineered. This model works in accordance with the static input-output Leontief 's model. The results can be used for choosing the ways of system's stability improving, and protecting it from various disturbances and imbalance.

Emergence of Cooperative Long-Term Market Loyalty in Double Auction Markets.

PubMed

Alorić, Aleksandra; Sollich, Peter; McBurney, Peter; Galla, Tobias

2016-01-01

Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and in particular as a consequence of repeated interaction and co-adaptation among the agents in a market. We devise a stylized model of double auction markets and adaptive traders that incorporates these features. Traders choose where to trade (which market) and how to trade (to buy or to sell) based on their previous experience. We find that when the typical scale of market returns (or, at fixed scale of returns, the intensity of choice) become higher than some threshold, the preferred state of the system is segregated: both buyers and sellers are segmented into subgroups that are persistently loyal to one market over another. We characterize the segregated state analytically in the limit of large markets: it is stabilized by some agents acting cooperatively to enable trade, and provides higher rewards than its unsegregated counterpart both for individual traders and the population as a whole.

Emergence of Cooperative Long-Term Market Loyalty in Double Auction Markets

PubMed Central

Alorić, Aleksandra; Sollich, Peter; McBurney, Peter; Galla, Tobias

2016-01-01

Loyal buyer-seller relationships can arise by design, e.g. when a seller tailors a product to a specific market niche to accomplish the best possible returns, and buyers respond to the dedicated efforts the seller makes to meet their needs. We ask whether it is possible, instead, for loyalty to arise spontaneously, and in particular as a consequence of repeated interaction and co-adaptation among the agents in a market. We devise a stylized model of double auction markets and adaptive traders that incorporates these features. Traders choose where to trade (which market) and how to trade (to buy or to sell) based on their previous experience. We find that when the typical scale of market returns (or, at fixed scale of returns, the intensity of choice) become higher than some threshold, the preferred state of the system is segregated: both buyers and sellers are segmented into subgroups that are persistently loyal to one market over another. We characterize the segregated state analytically in the limit of large markets: it is stabilized by some agents acting cooperatively to enable trade, and provides higher rewards than its unsegregated counterpart both for individual traders and the population as a whole. PMID:27120473

An Agent-based Modeling of Water-Food Nexus towards Sustainable Management of Urban Water Resources

NASA Astrophysics Data System (ADS)

Esmaeili, N.; Kanta, L.

2017-12-01

Growing population, urbanization, and climate change have put tremendous stress on water systems in many regions. A shortage in water system not only affects water users of a municipality but also that of food system. About 70% of global water is withdrawn for agriculture; livestock and dairy productions are also dependent on water availability. Although researchers and policy makers have identified and emphasized the water-food (WF) nexus in recent decade, most existing WF models offer strategies to reduce trade-offs and to generate benefits without considering feedback loops and adaptations between those systems. Feedback loops between water and food system can help understand long-term behavioral trends between water users of the integrated WF system which, in turn, can help manage water resources sustainably. An Agent-based modeling approach is applied here to develop a conceptual framework of WF systems. All water users in this system are modeled as agents, who are capable of making decisions and can adapt new behavior based on inputs from other agents in a shared environment through a set of logical and mathematical rules. Residential and commercial/industrial consumers are represented as municipal agents; crop, livestock, and dairy farmers are represented as food agents; and water management officials are represented as policy agent. During the period of water shortage, policy agent will propose/impose various water conservation measures, such as adapting water-efficient technologies, banning outdoor irrigation, implementing supplemental irrigation, using recycled water for livestock/dairy production, among others. Municipal and food agents may adapt conservation strategies and will update their demand accordingly. Emergent properties of the WF nexus will arise through dynamic interactions between various actors of water and food system. This model will be implemented to a case study for resource allocation and future policy development.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Simulating Microdosimetry of Environmental Chemicals for EPA’s Virtual Liver

EPA Science Inventory

US EPA Virtual Liver (v-Liver) is a cellular systems model of hepatic tissues aimed at predicting chemical-induced adverse effects through agent-based modeling. A primary objective of the project is to extrapolate in vitro data to in vivo outcomes. Agent-based approaches to tissu...

Verifying Multi-Agent Systems via Unbounded Model Checking

NASA Technical Reports Server (NTRS)

Kacprzak, M.; Lomuscio, A.; Lasica, T.; Penczek, W.; Szreter, M.

2004-01-01

We present an approach to the problem of verification of epistemic properties in multi-agent systems by means of symbolic model checking. In particular, it is shown how to extend the technique of unbounded model checking from a purely temporal setting to a temporal-epistemic one. In order to achieve this, we base our discussion on interpreted systems semantics, a popular semantics used in multi-agent systems literature. We give details of the technique and show how it can be applied to the well known train, gate and controller problem. Keywords: model checking, unbounded model checking, multi-agent systems

Continuous Opinion Dynamics Under Bounded Confidence:. a Survey

NASA Astrophysics Data System (ADS)

Lorenz, Jan

Models of continuous opinion dynamics under bounded confidence have been presented independently by Krause and Hegselmann and by Deffuant et al. in 2000. They have raised a fair amount of attention in the communities of social simulation, sociophysics and complexity science. The researchers working on it come from disciplines such as physics, mathematics, computer science, social psychology and philosophy. In these models agents hold continuous opinions which they can gradually adjust if they hear the opinions of others. The idea of bounded confidence is that agents only interact if they are close in opinion to each other. Usually, the models are analyzed with agent-based simulations in a Monte Carlo style, but they can also be reformulated on the agent's density in the opinion space in a master equation style. The contribution of this survey is fourfold. First, it will present the agent-based and density-based modeling frameworks including the cases of multidimensional opinions and heterogeneous bounds of confidence. Second, it will give the bifurcation diagrams of cluster configuration in the homogeneous model with uniformly distributed initial opinions. Third, it will review the several extensions and the evolving phenomena which have been studied so far, and fourth it will state some open questions.

Seldon v.3.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Nina; Ko, Teresa; Shneider, Max

Seldon is an agent-based social simulation framework that uniquely integrates concepts from a variety of different research areas including psychology, social science, and agent-based modeling. Development has been taking place for a number of years, previously focusing on gang and terrorist recruitment. The toolkit consists of simple agents (individuals) and abstract agents (groups of individuals representing social/institutional concepts) that interact according to exchangeable rule sets (i.e. linear attraction, linear reinforcement). Each agent has a set of customizable attributes that get modified during the interactions. Interactions create relationships between agents, and each agent has a maximum amount of relationship energy thatmore » it can expend. As relationships evolve, they form multiple levels of social networks (i.e. acquaintances, friends, cliques) that in turn drive future interactions. Agents can also interact randomly if they are not connected through a network, mimicking the chance interactions that real people have in everyday life. We are currently integrating Seldon with the cognitive framework (also developed at Sandia). Each individual agent has a lightweight cognitive model that is created automatically from textual sources. Cognitive information is exchanged during interactions, and can also be injected into a running simulation. The entire framework has been parallelized to allow for larger simulations in an HPC environment. We have also added more detail to the agents themselves (a"Big Five" personality model) and their interactions (an enhanced relationship model) for a more realistic representation.« less

Agent-Based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

NASA Astrophysics Data System (ADS)

Faroqi, H.; Mesgari, M.-S.

2015-12-01

During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

A multi-agent architecture for geosimulation of moving agents

NASA Astrophysics Data System (ADS)

Vahidnia, Mohammad H.; Alesheikh, Ali A.; Alavipanah, Seyed Kazem

2015-10-01

In this paper, a novel architecture is proposed in which an axiomatic derivation system in the form of first-order logic facilitates declarative explanation and spatial reasoning. Simulation of environmental perception and interaction between autonomous agents is designed with a geographic belief-desire-intention and a request-inform-query model. The architecture has a complementary quantitative component that supports collaborative planning based on the concept of equilibrium and game theory. This new architecture presents a departure from current best practices geographic agent-based modelling. Implementation tasks are discussed in some detail, as well as scenarios for fleet management and disaster management.

Analytical modeling and experimental validation of a magnetorheological mount

NASA Astrophysics Data System (ADS)

Nguyen, The; Ciocanel, Constantin; Elahinia, Mohammad

2009-03-01

Magnetorheological (MR) fluid has been increasingly researched and applied in vibration isolation devices. To date, the suspension system of several high performance vehicles has been equipped with MR fluid based dampers and research is ongoing to develop MR fluid based mounts for engine and powertrain isolation. MR fluid based devices have received attention due to the MR fluid's capability to change its properties in the presence of a magnetic field. This characteristic places MR mounts in the class of semiactive isolators making them a desirable substitution for the passive hydraulic mounts. In this research, an analytical model of a mixed-mode MR mount was constructed. The magnetorheological mount employs flow (valve) mode and squeeze mode. Each mode is powered by an independent electromagnet, so one mode does not affect the operation of the other. The analytical model was used to predict the performance of the MR mount with different sets of parameters. Furthermore, in order to produce the actual prototype, the analytical model was used to identify the optimal geometry of the mount. The experimental phase of this research was carried by fabricating and testing the actual MR mount. The manufactured mount was tested to evaluate the effectiveness of each mode individually and in combination. The experimental results were also used to validate the ability of the analytical model in predicting the response of the MR mount. Based on the observed response of the mount a suitable controller can be designed for it. However, the control scheme is not addressed in this study.

Literature Review on Systems of Systems (SoS): A Methodology With Preliminary Results

DTIC Science & Technology

2013-11-01

Appendix H. The Enhanced ISAAC Neural Simulation Toolkit (EINSTein) 73  Appendix I. The Map Aware Nonuniform Automata (MANA) Agent-Based Model 81...83  Figure I-3. Quadrant chart addressing SoS and associated SoSA designs for the Map Aware Nonuniform Automata (MANA) agent...Map Aware Nonuniform Automata (MANA) agent-based model. 85  Table I-2. SoS and SoSA software component maturation scores associated with the Map

Stochastic modeling and experimental analysis of phenotypic switching and survival of cancer cells under stress

NASA Astrophysics Data System (ADS)

Zamani Dahaj, Seyed Alireza; Kumar, Niraj; Sundaram, Bala; Celli, Jonathan; Kulkarni, Rahul

The phenotypic heterogeneity of cancer cells is critical to their survival under stress. A significant contribution to heterogeneity of cancer calls derives from the epithelial-mesenchymal transition (EMT), a conserved cellular program that is crucial for embryonic development. Several studies have investigated the role of EMT in growth of early stage tumors into invasive malignancies. Also, EMT has been closely associated with the acquisition of chemoresistance properties in cancer cells. Motivated by these studies, we analyze multi-phenotype stochastic models of the evolution of cancers cell populations under stress. We derive analytical results for time-dependent probability distributions that provide insights into the competing rates underlying phenotypic switching (e.g. during EMT) and the corresponding survival of cancer cells. Experimentally, we evaluate these model-based predictions by imaging human pancreatic cancer cell lines grown with and without cytotoxic agents and measure growth kinetics, survival, morphological changes and (terminal evaluation of) biomarkers with associated epithelial and mesenchymal phenotypes. The results derived suggest approaches for distinguishing between adaptation and selection scenarios for survival in the presence of external stresses.

A structurally based analytic model for estimation of biomass and fuel loads of woodland trees

Treesearch

Robin J. Tausch

2009-01-01

Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of...

Insights on Antioxidant Assays for Biological Samples Based on the Reduction of Copper Complexes—The Importance of Analytical Conditions

PubMed Central

Marques, Sara S.; Magalhães, Luís M.; Tóth, Ildikó V.; Segundo, Marcela A.

2014-01-01

Total antioxidant capacity assays are recognized as instrumental to establish antioxidant status of biological samples, however the varying experimental conditions result in conclusions that may not be transposable to other settings. After selection of the complexing agent, reagent addition order, buffer type and concentration, copper reducing assays were adapted to a high-throughput scheme and validated using model biological antioxidant compounds of ascorbic acid, Trolox (a soluble analogue of vitamin E), uric acid and glutathione. A critical comparison was made based on real samples including NIST-909c human serum certified sample, and five study samples. The validated method provided linear range up to 100 µM Trolox, (limit of detection 2.3 µM; limit of quantification 7.7 µM) with recovery results above 85% and precision <5%. The validated developed method with an increased sensitivity is a sound choice for assessment of TAC in serum samples. PMID:24968275

In vitro DNA binding, pBR322 plasmid cleavage and molecular modeling study of chiral benzothiazole Schiff-base-valine Cu(II) and Zn(II) complexes to evaluate their enantiomeric biological disposition for molecular target DNA

NASA Astrophysics Data System (ADS)

Alizadeh, Rahman; Afzal, Mohd; Arjmand, Farukh

2014-10-01

Bicyclic heterocyclic compounds viz. benzothiazoles are key components of deoxyribonucleic acid (DNA) molecules and participate directly in the encoding of genetic information. Benzothiazoles, therefore, represent a potent and selective class of antitumor compounds. The design and synthesis of chiral antitumor chemotherapeutic agents of Cu(II) and Zn(II), L- and -D benzothiazole Schiff base-valine complexes 1a &b and 2a &b, respectively were carried out and thoroughly characterized by spectroscopic and analytical techniques. Interaction of 1a and b and 2a and b with CT DNA by employing UV-vis, florescence, circular dichroic methods and cleavage studies of 1a with pBR322 plasmid, molecular docking were done in order to demonstrate their enantiomeric disposition toward the molecular drug target DNA. Interestingly, these studies unambiguously demonstrated the greater potency of L-enantiomer in comparison to D-enantiomer.

A conceptual data model and modelling language for fields and agents

NASA Astrophysics Data System (ADS)

de Bakker, Merijn; de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2016-04-01

Modelling is essential in order to understand environmental systems. Environmental systems are heterogeneous because they consist of fields and agents. Fields have a value defined everywhere at all times, for example surface elevation and temperature. Agents are bounded in space and time and have a value only within their bounds, for example biomass of a tree crown or the speed of a car. Many phenomena have properties of both fields and agents. Although many systems contain both fields and agents and integration of these concepts would be required for modelling, existing modelling frameworks concentrate on either agent-based or field-based modelling and are often low-level programming frameworks. A concept is lacking that integrates fields and agents in a way that is easy to use for modelers who are not software engineers. To address this issue, we develop a conceptual data model that represents fields and agents uniformly. We then show how the data model can be used in a high-level modelling language. The data model represents fields and agents in space-time. Also relations and networks can be represented using the same concepts. Using the conceptual data model we can represent static and mobile agents that may have spatial and temporal variation within their extent. The concepts we use are phenomenon, property set, item, property, domain and value. The phenomenon is the thing that is modelled, which can be any real world thing, for example trees. A phenomenon usually consists of several items, e.g. single trees. The domain is the spatiotemporal location and/or extent for which the items in the phenomenon are defined. Multiple different domains can coexist for a given phenomenon. For example a domain describing the extent of the trees and a domain describing the stem locations. The same goes for the property, which is an attribute of the thing that is being modeled. A property has a value, which is possibly discretized, for example the biomass over the tree crown extent. Properties sharing the same domain are grouped into a property set. The conceptual data model is translated into a physical data model in de Jong et al. (2016, presented in the same session). We have designed a modelling language that allows domain specialists to build models without the programming efforts required by many programming environments. The language is based on the ideas of map algebra. We have defined data types that are associated with a phenomenon. These data types determine the behavior of the language when used as arguments in operations. The result is a concise language in which fields and agents can be combined in operations. We test the language in a case study modelling exposure to air pollution of commuting children. References De Jong, K, M. de Bakker, D. Karssenberg. 2016. A physical data model for fields and agents. European Geosciences Union, EGU General Assembly, 2016, Vienna.

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

PubMed Central

Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

2014-01-01

Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

Analytical investigation of the faster-is-slower effect with a simplified phenomenological model

NASA Astrophysics Data System (ADS)

Suzuno, K.; Tomoeda, A.; Ueyama, D.

2013-11-01

We investigate the mechanism of the phenomenon called the “faster-is-slower”effect in pedestrian flow studies analytically with a simplified phenomenological model. It is well known that the flow rate is maximized at a certain strength of the driving force in simulations using the social force model when we consider the discharge of self-driven particles through a bottleneck. In this study, we propose a phenomenological and analytical model based on a mechanics-based modeling to reveal the mechanism of the phenomenon. We show that our reduced system, with only a few degrees of freedom, still has similar properties to the original many-particle system and that the effect comes from the competition between the driving force and the nonlinear friction from the model. Moreover, we predict the parameter dependences on the effect from our model qualitatively, and they are confirmed numerically by using the social force model.