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.
Employment growth through labor flow networks.
Guerrero, Omar A; Axtell, Robert L
2013-01-01
It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.
Employment Growth through Labor Flow Networks
Guerrero, Omar A.; Axtell, Robert L.
2013-01-01
It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market. PMID:23658682
The Strategic Partners Network's Extraction: The XStrat.Net Project
NASA Astrophysics Data System (ADS)
Taifi, Nouha; Passiante, Giuseppina
The firms in the business environment have to choose adequate partners in order to sustain their competitive advantage and their economic performance. Plus, the creation of special communities consisting of these partners is essential for the life-long development of these latter and the firms creating them. The research project XStrat.Net aims at the identification of factors and indicators about the organizations for the modelling of intelligent agents -XStrat intelligent agents- and the engineering of a software -XStrat- to process these backbones intelligent agents. Through the use of the software, the firms will be able to select the needed partners for the creation of special communities for the purpose of learning, interest or innovation. The XStrat.Net project also intends to provide guidelines for the creation of the special communities.
ERIC Educational Resources Information Center
Assante, Leonard E.; Schrader, Stuart M.
The International Health Communication Hotline (InHealth) represents an attempt to firmly establish, develop and promote a new Communication Studies subdiscipline in the academic and health care arenas via computer networking. If successful, the project will demonstrate the power of computer networking as an agent of change. Health communication…
The role of endogenous and exogenous mechanisms in the formation of R&D networks
NASA Astrophysics Data System (ADS)
Tomasello, Mario V.; Perra, Nicola; Tessone, Claudio J.; Karsai, Márton; Schweitzer, Frank
2014-07-01
We develop an agent-based model of strategic link formation in Research and Development (R&D) networks. Empirical evidence has shown that the growth of these networks is driven by mechanisms which are both endogenous to the system (that is, depending on existing alliances patterns) and exogenous (that is, driven by an exploratory search for newcomer firms). Extant research to date has not investigated both mechanisms simultaneously in a comparative manner. To overcome this limitation, we develop a general modeling framework to shed light on the relative importance of these two mechanisms. We test our model against a comprehensive dataset, listing cross-country and cross-sectoral R&D alliances from 1984 to 2009. Our results show that by fitting only three macroscopic properties of the network topology, this framework is able to reproduce a number of micro-level measures, including the distributions of degree, local clustering, path length and component size, and the emergence of network clusters. Furthermore, by estimating the link probabilities towards newcomers and established firms from the data, we find that endogenous mechanisms are predominant over the exogenous ones in the network formation, thus quantifying the importance of existing structures in selecting partner firms.
The Evolution of ICT Markets: An Agent-Based Model on Complex Networks
NASA Astrophysics Data System (ADS)
Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li
Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.
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.
Kmec, Julie A; Trimble, Lindsey B
2009-06-01
This article investigates how social network use to find work affects pay. Analyses using the Multi-City Study of Urban Inequality consider the extent to which a network contact's influence level affects a job applicant's pay, whether this effect differs for white, black, and Latino contacts, and how workplace racial context moderates this relationship. Three main findings emerge. First, having an influential contact--one with hiring authority--compared to having no contact yields higher pay. Second, white and minority contact influence on pay differs: among minority contacts, being an outsider (i.e., someone not employed by the firm to which the applicant applies) is associated with higher pay, but being an employee of the firm--an insider--is not. Third, regardless of workplace racial context, black and Latino contacts' influence is most beneficial when their race/ethnicity is not known to the hiring agent. We offer a new interpretation of the mixed findings with regard to the relationship between social network use and pay.
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.
NASA Astrophysics Data System (ADS)
Liu, Helin; Silva, Elisabete A.; Wang, Qian
2016-07-01
This paper presents an extension to the agent-based model "Creative Industries Development-Urban Spatial Structure Transformation" by incorporating GIS data. Three agent classes, creative firms, creative workers and urban government, are considered in the model, and the spatial environment represents a set of GIS data layers (i.e. road network, key housing areas, land use). With the goal to facilitate urban policy makers to draw up policies locally and optimise the land use assignment in order to support the development of creative industries, the improved model exhibited its capacity to assist the policy makers conducting experiments and simulating different policy scenarios to see the corresponding dynamics of the spatial distributions of creative firms and creative workers across time within a city/district. The spatiotemporal graphs and maps record the simulation results and can be used as a reference by the policy makers to adjust land use plans adaptively at different stages of the creative industries' development process.
Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong
2016-01-01
As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions. PMID:26745375
Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong
2016-01-01
As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.
Networks of Firms and the Ridge in the Production Space
NASA Astrophysics Data System (ADS)
Souma, Wataru
We develop complex networks that represent activities in the economy. The network in this study is constructed from firms and the relationships between firms, i.e., shareholding, interlocking directors, transactions, and joint applications for patents. Thus, the network is regarded as a multigraph, and it is also regarded as a weighted network. By calculating various network indices, we clarify the characteristics of the network. We also consider the dynamics of firms in the production space that are characterized by capital stock, employment, and profit. Each firm moves within this space to maximize their profit by using controlling of capital stock and employment. We show that the dynamics of rational firms can be described using a ridge equation. We analytically solve this equation by assuming the extensive Cobb-Douglas production function, and thereby obtain a solution. By comparing the distribution of firms and this solution, we find that almost all of the 1,100 firms listed on the first section of the Tokyo stock exchange and belonging to the manufacturing sector are managed efficiently.
Endogenous network of firms and systemic risk
NASA Astrophysics Data System (ADS)
Ma, Qianting; He, Jianmin; Li, Shouwei
2018-02-01
We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.
Bank-firm credit network in Japan: an analysis of a bipartite network.
Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N
2015-01-01
We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.
Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network
Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N.
2015-01-01
We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. PMID:25933413
Successful strategies for competing networks
NASA Astrophysics Data System (ADS)
Aguirre, J.; Papo, D.; Buldú, J. M.
2013-04-01
Competitive interactions represent one of the driving forces behind evolution and natural selection in biological and sociological systems. For example, animals in an ecosystem may vie for food or mates; in a market economy, firms may compete over the same group of customers; sensory stimuli may compete for limited neural resources to enter the focus of attention. Here, we derive rules based on the spectral properties of the network governing the competitive interactions between groups of agents organized in networks. In the scenario studied here the winner of the competition, and the time needed to prevail, essentially depend on the way a given network connects to its competitors and on its internal structure. Our results allow assessment of the extent to which real networks optimize the outcome of their interaction, but also provide strategies through which competing networks can improve on their situation. The proposed approach is applicable to a wide range of systems that can be modelled as networks.
Albornoz, Facundo; Cole, Matthew A; Elliott, Robert J R; Ercolani, Marco G
2014-12-15
In the light of climate uncertainty and growing concern for the natural environment, an increasingly important aspect of global business is the environmental behaviour of firms. In this paper we consider the factors that influence firms' environmental actions (EAs). Our study of Argentinean firms concentrates on measures of environmental spillovers, informal and formal networks and absorptive capacity by testing four related hypotheses. We find that foreign-owned firms, large firms and those with a greater capacity to assimilate new environmental technologies are more likely to adopt EAs. We also show that formal and informal networks aid the adoption of EAs in the presence of traditional firm-level spillovers. Finally, we show that foreign-owned firms have different motives to domestic firms for undertaking EAs. Copyright © 2014 Elsevier Ltd. All rights reserved.
A study of knowledge supernetworks and network robustness in different business incubators
NASA Astrophysics Data System (ADS)
Zhang, Haihong; Wu, Wenqing; Zhao, Liming
2016-04-01
As the most important intangible resource of the new generation of business incubators, knowledge has been studied extensively, particularly with respect to how it spreads among incubating firms through knowledge networks. However, these homogeneous networks do not adequately describe the heterogeneity of incubating firms in different types of business incubators. To solve the problem of heterogeneity, the notion of a knowledge supernetwork has been used both to construct a knowledge interaction model among incubating firms and to distinguish social network relationships from knowledge network relationships. The process of knowledge interaction and network evolution can then be simulated with a few rules for incubating firms regarding knowledge innovation/absorption, social network connection, and entry and exit, among other aspects. Knowledge and networks have been used as performance indicators to evaluate the evolution of knowledge supernetworks. Moreover, we study the robustness of incubating firms' social networks by employing four types of attack strategies. Based on our simulation results, we conclude that there have been significant knowledge interaction and network evolution among incubating firms on a periodic basis and that both specialized and diversified business incubators have every advantage necessary in terms of both knowledge and networks to cultivate start-up companies. As far as network robustness is concerned, there is no obvious difference between the two types of business incubators with respect to the stability of their network structures, but specialized business incubators have stronger network communication abilities than diversified business incubators.
On the topological structure of multinationals network
NASA Astrophysics Data System (ADS)
Joyez, Charlie
2017-05-01
This paper uses a weighted network analysis to examine the structure of multinationals' implantation countries network. Based on French firm-level dataset of multinational enterprises (MNEs) the network analysis provides information on each country position in the network and in internationalization strategies of French MNEs through connectivity preferences among the nodes. The paper also details network-wide features and their recent evolution toward a more decentralized structure. While much has been said on international trade network, this paper shows that multinational firms' studies would also benefit from network analysis, notably by investigating the sensitivity of the network construction to firm heterogeneity.
The impact of baking time and bread storage temperature on bread crumb properties.
Bosmans, Geertrui M; Lagrain, Bert; Fierens, Ellen; Delcour, Jan A
2013-12-15
Two baking times (9 and 24 min) and storage temperatures (4 and 25 °C) were used to explore the impact of heat exposure during bread baking and subsequent storage on amylopectin retrogradation, water mobility, and bread crumb firming. Shorter baking resulted in less retrogradation, a less extended starch network and smaller changes in crumb firmness and elasticity. A lower storage temperature resulted in faster retrogradation, a more rigid starch network with more water inclusion and larger changes in crumb firmness and elasticity. Crumb to crust moisture migration was lower for breads baked shorter and stored at lower temperature, resulting in better plasticized biopolymer networks in crumb. Network stiffening, therefore, contributed less to crumb firmness. A negative relation was found between proton mobilities of water and biopolymers in the crumb gel network and crumb firmness. The slope of this linear function was indicative for the strength of the starch network. Copyright © 2013 Elsevier Ltd. All rights reserved.
40 CFR 745.89 - Firm certification.
Code of Federal Regulations, 2010 CFR
2010-07-01
... LEAD-BASED PAINT POISONING PREVENTION IN CERTAIN RESIDENTIAL STRUCTURES Residential Property Renovation... submit to EPA a completed “Application for Firms,” signed by an authorized agent of the firm, and pay at... reimburse the firm for the excess amount. (2) After EPA receives a firm's application, EPA will take one of...
Mean field approximation for biased diffusion on Japanese inter-firm trading network.
Watanabe, Hayafumi
2014-01-01
By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.
Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning
García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor
2015-01-01
This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure. PMID:26656107
Micro-Level Adaptation, Macro-Level Selection, and the Dynamics of Market Partitioning.
García-Díaz, César; van Witteloostuijn, Arjen; Péli, Gábor
2015-01-01
This paper provides a micro-foundation for dual market structure formation through partitioning processes in marketplaces by developing a computational model of interacting economic agents. We propose an agent-based modeling approach, where firms are adaptive and profit-seeking agents entering into and exiting from the market according to their (lack of) profitability. Our firms are characterized by large and small sunk costs, respectively. They locate their offerings along a unimodal demand distribution over a one-dimensional product variety, with the distribution peak constituting the center and the tails standing for the peripheries. We found that large firms may first advance toward the most abundant demand spot, the market center, and release peripheral positions as predicted by extant dual market explanations. However, we also observed that large firms may then move back toward the market fringes to reduce competitive niche overlap in the center, triggering nonlinear resource occupation behavior. Novel results indicate that resource release dynamics depend on firm-level adaptive capabilities, and that a minimum scale of production for low sunk cost firms is key to the formation of the dual structure.
Knowledge service decision making in business incubators based on the supernetwork model
NASA Astrophysics Data System (ADS)
Zhao, Liming; Zhang, Haihong; Wu, Wenqing
2017-08-01
As valuable resources for incubating firms, knowledge resources have received gradually increasing attention from all types of business incubators, and business incubators use a variety of knowledge services to stimulate rapid growth in incubating firms. Based on previous research, we generalize the knowledge transfer and knowledge networking services of two main forms of knowledge services and further divide knowledge transfer services into knowledge depth services and knowledge breadth services. Then, we construct the business incubators' knowledge supernetwork model, describe the evolution mechanism among heterogeneous agents and utilize a simulation to explore the performance variance of different business incubators' knowledge services. The simulation results show that knowledge stock increases faster when business incubators are able to provide knowledge services to more incubating firms and that the degree of discrepancy in the knowledge stock increases during the process of knowledge growth. Further, knowledge transfer services lead to greater differences in the knowledge structure, while knowledge networking services lead to smaller differences. Regarding the two types of knowledge transfer services, knowledge depth services are more conducive to knowledge growth than knowledge breadth services, but knowledge depth services lead to greater gaps in knowledge stocks and greater differences in knowledge structures. Overall, it is optimal for business incubators to select a single knowledge service or portfolio strategy based on the amount of time and energy expended on the two types of knowledge services.
Innovation flow through social networks: productivity distribution in France and Italy
NASA Astrophysics Data System (ADS)
di Matteo, T.; Aste, T.; Gallegati, M.
2005-10-01
From a detailed empirical analysis of the productivity of non financial firms across several countries and years we show that productivity follows a non-Gaussian distribution with `fat tails' in the large productivity region which are well mimicked by power law behaviors. We discuss how these empirical findings can be linked to a mechanism of exchanges in a social network where firms improve their productivity by direct innovation and/or by imitation of other firm's technological and organizational solutions. The type of network-connectivity determines how fast and how efficiently information can diffuse and how quickly innovation will permeate or behaviors will be imitated. From a model for innovation flow through a complex network we show that the expectation values of the productivity of each firm are proportional to its connectivity in the network of links between firms. The comparison with the empirical distributions in France and Italy reveals that in this model, such a network must be of a scale-free type with a power-law degree distribution in the large connectivity range.
Community Structure of a Bank-Firm Credit Network in Japan
NASA Astrophysics Data System (ADS)
Iyetomi, Hiroshi; Matsuura, Yuki
2014-03-01
We study temporal change of community structure in a Japanese credit network formed by banks and listed firms through their financial relations over the last 30 years. The credit connectedness is regarded as a potenital source of systemic risk. Our network is a bipartite graph consisting of two species of nodes connected with bidirectional links. The direction of links is identified with that of risk flows and their weights are relative credit/loan with respect to the targets. In a partial credit network obtained only with the links pointing from firms toward banks, the city banks forms one major community in most of the time period to share risk when firms go wrong. On the other hand, a partial network only with the links from banks toward firms is decomposed into communities of similar size each of which has its own city bank, reflecting the main-bank system in Japan. Finally we take overlapping parts of the two community sets to find cores of the risk concentration in the credit network. This work was supported by JSPS KAKENHI Grant Number 22300080.
Inter-firm Networks, Organizational Learning and Knowledge Updating: An Empirical Study
NASA Astrophysics Data System (ADS)
Zhang, Su-rong; Wang, Wen-ping
In the era of knowledge-based economy which information technology develops rapidly, the rate of knowledge updating has become a critical factor for enterprises to gaining competitive advantage .We build an interactional theoretical model among inter-firm networks, organizational learning and knowledge updating thereby and demonstrate it with empirical study at last. The result shows that inter-firm networks and organizational learning is the source of knowledge updating.
The origin of asymmetric behavior of money flow in the business firm network
NASA Astrophysics Data System (ADS)
Miura, W.; Takayasu, H.; Takayasu, M.
2012-09-01
In the business firm network, the number of in-degrees and out-degrees show the same scale-free property, however, the distribution of authorities and hubs show asymmetric behavior. Here we show the result of an analysis of the two-link structure of the network to find the origin of this asymmetric behavior. We find the tendency for big construction firms intermediating small subcontracting firms to have higher hub degrees. By measuring the strength of preferential attachment rate of new companies, we also find a abnormally strong preferential attachment for which the exponent is 1.4 with respect to out-degree when a new company forms a business partnership with a construction company. We propose a new model that reproduces the asymmetric behavior of the degrees of authorities and hubs by changing the preferential attachment rate between the in-degree and the out-degree in the business firm network.
Network analysis to detect common strategies in Italian foreign direct investment
NASA Astrophysics Data System (ADS)
De Masi, G.; Giovannetti, G.; Ricchiuti, G.
2013-03-01
In this paper we reconstruct and discuss the network of Italian firms investing abroad, exploiting information from complex network analysis. This method, detecting the key nodes of the system (both in terms of firms and countries of destination), allows us to single out the linkages among firms without ex-ante priors. Moreover, through the examination of affiliates’ economic activity, it allows us to highlight different internationalization strategies of “leaders” in different manufacturing sectors.
Time-varying causal network of the Korean financial system based on firm-specific risk premiums
NASA Astrophysics Data System (ADS)
Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin
2016-09-01
The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.
Firm profitability and the network of organizational capabilities
NASA Astrophysics Data System (ADS)
Wagner, Friedrich; Milaković, Mishael; Alfarano, Simone
2010-11-01
A Laplace distribution for firm profit rates (or returns on assets) can be obtained through the sum of many independent shocks if the number of shocks is Poisson distributed. Interpreting this as a linear chain of events, we generalize the process to a hierarchical network structure. The hierarchical model reproduces the observed distributional patterns of firm profitability, which crucially depend on the life span of firms. While the profit rates of long-lived firms obey a symmetric Laplacian, short-lived firms display a different behavior depending on whether they are capable of generating positive profits or not. Successful short-lived firms exhibit a symmetric yet more leptokurtic pdf than long-lived firms. Our model suggests that these firms are more dynamic in their organizational capabilities, but on average also face more risk than long-lived firms. Finally, short-lived firms that fail to generate positive profits have the most leptokurtic distribution among the three classes, and on average lose slightly more than their total assets within a year.
NASA Astrophysics Data System (ADS)
Chakrabarti, Anindya S.
2012-12-01
We address the issue of the distribution of firm size. To this end we propose a model of firms in a closed, conserved economy populated with zero-intelligence agents who continuously move from one firm to another. We then analyze the size distribution and related statistics obtained from the model. There are three well known statistical features obtained from the panel study of the firms i.e., the power law in size (in terms of income and/or employment), the Laplace distribution in the growth rates and the slowly declining standard deviation of the growth rates conditional on the firm size. First, we show that the model generalizes the usual kinetic exchange models with binary interaction to interactions between an arbitrary number of agents. When the number of interacting agents is in the order of the system itself, it is possible to decouple the model. We provide exact results on the distributions which are not known yet for binary interactions. Our model easily reproduces the power law for the size distribution of firms (Zipf’s law). The fluctuations in the growth rate falls with increasing size following a power law (though the exponent does not match with the data). However, the distribution of the difference of the firm size in this model has Laplace distribution whereas the real data suggests that the difference of the log of sizes has the same distribution.
Organizing product innovation: hierarchy, market or triple-helix networks?
Fitjar, Rune Dahl; Gjelsvik, Martin; Rodríguez-Pose, Andrés
This paper assesses the extent to which the organization of the innovation effort in firms, as well as the geographical scale at which this effort is pursued, affects the capacity to benefit from product innovations. Three alternative modes of organization are studied: hierarchy, market and triple-helix-type networks. Furthermore, we consider triple-helix networks at three geographical scales: local, national and international. These relationships are tested on a random sample of 763 firms located in five urban regions of Norway which reported having introduced new products or services during the preceding 3 years. The analysis shows that firms exploiting internal hierarchy or triple-helix networks with a wide range of partners managed to derive a significantly higher share of their income from new products, compared to those that mainly relied on outsourcing within the market. In addition, the analysis shows that the geographical scale of cooperation in networks, as well as the type of partner used, matters for the capacity of firms to benefit from product innovation. In particular, firms that collaborate in international triple-helix-type networks involving suppliers, customers and R&D institutions extract a higher share of their income from product innovations, regardless of whether they organize the processes internally or through the network.
Business cycles' correlation and systemic risk of the Japanese supplier-customer network.
Krichene, Hazem; Chakraborty, Abhijit; Inoue, Hiroyasu; Fujiwara, Yoshi
2017-01-01
This work aims to study and explain the business cycle correlations of the Japanese production network. We consider the supplier-customer network, which is a directed network representing the trading links between Japanese firms (links from suppliers to customers). The community structure of this network is determined by applying the Infomap algorithm. Each community is defined by its GDP and its associated business cycle. Business cycle correlations between communities are estimated based on copula theory. Then, based on firms' attributes and network topology, these correlations are explained through linear econometric models. The results show strong evidence of business cycle correlations in the Japanese production network. A significant systemic risk is found for high negative or positive shocks. These correlations are explained mainly by the sector and by geographic similarities. Moreover, our results highlight the higher vulnerability of small communities and small firms, which is explained by the disassortative mixing of the production network.
Risky business: when mom and pop buy health insurance for their employees.
Gabel, Jon R; Pickreign, Jeremy D
2004-04-01
The economics of small group insurance makes offering health benefits to employees a risky business. Surveys of employers from 1989 to 2003 reveal that more rapid premium increases are forcing small firms to impose higher cost-sharing. In 2003, premiums for small firms (3-199 workers) increased 15.5 percent, outpacing the 13.2 percent increase for large firms (200+ workers). From 2000 to 2003, deductibles among small firms increased 100 percent in PPO plans when employees use in-network providers and 131 percent when they use out-of-network providers; among large firms, deductibles in PPO plans increased 33 percent and 44 percent, respectively. And in 2003, 40.3 percent of employees in the smallest firms contributed 41 percent or more of the total family premium, compared with only 11.2 percent of employees in large firms. Clearly, fundamental change in the small employer market is necessary, including new options for helping small firms gain access to the advantages large firms have in purchasing health benefits.
ERIC Educational Resources Information Center
Toner, Phillip; Marceau, Jane; Hall, Richard; Considine, Gillian
2004-01-01
This volume is a companion to "Innovation Agents: VET Skills and Innovation in Australian Industries and Firms. Volume 1". The detailed report of the project is contained in Volume 1 while Volume 2 contains the appendices: (1) Data tables for construction of the composite index of innovation; (2) Case study interview schedule; and (3)…
The Structure and Evolution of Buyer-Supplier Networks
Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu
2014-01-01
In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains. PMID:25000368
The structure and evolution of buyer-supplier networks.
Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu
2014-01-01
In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks - shocks affecting only a particular firm - through customer-supplier chains.
Goto, Hayato; Viegas, Eduardo; Jensen, Henrik Jeldtoft; Takayasu, Hideki; Takayasu, Misako
2017-07-11
Recently, growth mechanism of firms in complex business networks became new targets of scientific study owing to increasing availability of high quality business firms' data. Here, we paid attention to comprehensive data of M&A events for 40 years and derived empirical laws by applying methods and concepts of aggregation dynamics of aerosol physics. It is found that the probability of merger between bigger firms is bigger than that between smaller ones, and such tendency is enhancing year by year. We introduced a numerical model simulating the whole ecosystem of firms and showed that the system is already in an unstable monopoly state in which growth of middle sized firms are suppressed.
Scale-free models for the structure of business firm networks.
Kitsak, Maksim; Riccaboni, Massimo; Havlin, Shlomo; Pammolli, Fabio; Stanley, H Eugene
2010-03-01
We study firm collaborations in the life sciences and the information and communication technology sectors. We propose an approach to characterize industrial leadership using k -shell decomposition, with top-ranking firms in terms of market value in higher k -shell layers. We find that the life sciences industry network consists of three distinct components: a "nucleus," which is a small well-connected subgraph, "tendrils," which are small subgraphs consisting of small degree nodes connected exclusively to the nucleus, and a "bulk body," which consists of the majority of nodes. Industrial leaders, i.e., the largest companies in terms of market value, are in the highest k -shells of both networks. The nucleus of the life sciences sector is very stable: once a firm enters the nucleus, it is likely to stay there for a long time. At the same time we do not observe the above three components in the information and communication technology sector. We also conduct a systematic study of these three components in random scale-free networks. Our results suggest that the sizes of the nucleus and the tendrils in scale-free networks decrease as the exponent of the power-law degree distribution lambda increases, and disappear for lambda>or=3 . We compare the k -shell structure of random scale-free model networks with two real-world business firm networks in the life sciences and in the information and communication technology sectors. We argue that the observed behavior of the k -shell structure in the two industries is consistent with the coexistence of both preferential and random agreements in the evolution of industrial networks.
Beyond business process redesign: redefining Baxter's business network.
Short, J E; Venkatraman, N
1992-01-01
Business process redesign has focused almost exclusively on improving the firm's internal operations. Although internal efficiency and effectiveness are important objectives, the authors argue that business network redesign--reconceptualizing the role of the firm and its key business processes in the larger business network--is of greater strategic importance. To support their argument, they analyze the evolution of Baxter's ASAP system, one of the most publicized but inadequately understood strategic information systems of the 1980s. They conclude by examining whether ASAP's early successes have positioned the firm well for the changing hospital supplies marketplace of the 1990s.
45 CFR 1641.3 - Scope of debarment, suspension and removal.
Code of Federal Regulations, 2011 CFR
2011-10-01
... employee, independent contractor, agent or other representative of an IPA firm. (b) Actions against IPA... elements materially involved in the relevant engagement and as to which there is cause to debar, suspend or... the IPA firm only if such firm was materially involved in the relevant engagement and is specifically...
Modeling of Relation between Transaction Network and Production Activity for Firms
NASA Astrophysics Data System (ADS)
Iino, T.; Iyetomi, H.
Bak et al. [Ricerche Economiche 47 (1993), 3] proposed a self-organizing model for production activity of interacting firms to illustrate how large fluctuations can be triggered by small independent shocks in aggregate economy. This paper develops the original transaction model based on a regular network with layered order flow to accommodate more realistic networks. Simulations in the generalized model so obtained are then carried out for various networks to examine the influence caused by change of the network structure.
Social capital in Asia: Investigating returns to brokerage in collectivistic national cultures.
Merluzzi, Jennifer
2013-05-01
Evidence on the returns to brokerage networks predominately comes from studies of firms located in the United States. Analyses conducted in other countries have noted differences in how social capital may be valued questioning whether brokerage networks yield economic advantage in less individualistic contexts such as Asia. Using network data on employees involved in a product launch in the Asian region of a large American software firm, evidence of returns to brokerage is found among the top executives located and working in the collectivistic national country offices. This finding provides new insights on how returns to brokerage in a non-US culture may arise by considering the differing influences of firm and national culture as well as an employee's formal position at a firm. Copyright © 2012 Elsevier Inc. All rights reserved.
Electricity generation and transmission planning in deregulated power markets
NASA Astrophysics Data System (ADS)
He, Yang
This dissertation addresses the long-term planning of power generation and transmission facilities in a deregulated power market. Three models with increasing complexities are developed, primarily for investment decisions in generation and transmission capacity. The models are presented in a two-stage decision context where generation and transmission capacity expansion decisions are made in the first stage, while power generation and transmission service fees are decided in the second stage. Uncertainties that exist in the second stage affect the capacity expansion decisions in the first stage. The first model assumes that the electric power market is not constrained by transmission capacity limit. The second model, which includes transmission constraints, considers the interactions between generation firms and the transmission network operator. The third model assumes that the generation and transmission sectors make capacity investment decisions separately. These models result in Nash-Cournot equilibrium among the unregulated generation firms, while the regulated transmission network operator supports the competition among generation firms. Several issues in the deregulated electric power market can be studied with these models such as market powers of generation firms and transmission network operator, uncertainties of the future market, and interactions between the generation and transmission sectors. Results deduced from the developed models include (a) regulated transmission network operator will not reserve transmission capacity to gain extra profits; instead, it will make capacity expansion decisions to support the competition in the generation sector; (b) generation firms will provide more power supplies when there is more demand; (c) in the presence of future uncertainties, the generation firms will add more generation capacity if the demand in the future power market is expected to be higher; and (d) the transmission capacity invested by the transmission network operator depends on the characteristic of the power market and the topology of the transmission network. Also, the second model, which considers interactions between generation and transmission sectors, yields higher social welfare in the electric power market, than the third model where generation firms and transmission network operator make investment decisions separately.
Scale-free models for the structure of business firm networks
NASA Astrophysics Data System (ADS)
Kitsak, Maksim; Riccaboni, Massimo; Havlin, Shlomo; Pammolli, Fabio; Stanley, H. Eugene
2010-03-01
We study firm collaborations in the life sciences and the information and communication technology sectors. We propose an approach to characterize industrial leadership using k -shell decomposition, with top-ranking firms in terms of market value in higher k -shell layers. We find that the life sciences industry network consists of three distinct components: a “nucleus,” which is a small well-connected subgraph, “tendrils,” which are small subgraphs consisting of small degree nodes connected exclusively to the nucleus, and a “bulk body,” which consists of the majority of nodes. Industrial leaders, i.e., the largest companies in terms of market value, are in the highest k -shells of both networks. The nucleus of the life sciences sector is very stable: once a firm enters the nucleus, it is likely to stay there for a long time. At the same time we do not observe the above three components in the information and communication technology sector. We also conduct a systematic study of these three components in random scale-free networks. Our results suggest that the sizes of the nucleus and the tendrils in scale-free networks decrease as the exponent of the power-law degree distribution λ increases, and disappear for λ≥3 . We compare the k -shell structure of random scale-free model networks with two real-world business firm networks in the life sciences and in the information and communication technology sectors. We argue that the observed behavior of the k -shell structure in the two industries is consistent with the coexistence of both preferential and random agreements in the evolution of industrial networks.
Learning in innovation networks: Some simulation experiments
NASA Astrophysics Data System (ADS)
Gilbert, Nigel; Ahrweiler, Petra; Pyka, Andreas
2007-05-01
According to the organizational learning literature, the greatest competitive advantage a firm has is its ability to learn. In this paper, a framework for modeling learning competence in firms is presented to improve the understanding of managing innovation. Firms with different knowledge stocks attempt to improve their economic performance by engaging in radical or incremental innovation activities and through partnerships and networking with other firms. In trying to vary and/or to stabilize their knowledge stocks by organizational learning, they attempt to adapt to environmental requirements while the market strongly selects on the results. The simulation experiments show the impact of different learning activities, underlining the importance of innovation and learning.
ERIC Educational Resources Information Center
Buono, Anthony F., Ed.
This book contain papers 13 papers on enhancing inter-firm networks, including by intervening in mergers and acquisitions and developing strategic alliances and partnerships. The following papers are included: "Introduction" (Anthony F. Buono); "Making Mergers and Acquisitions Work: A Guide to Consulting Interventions" (Mitchell Lee Marks);…
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-30
... agents or distributors; market research and exposure; and joint venture and licensing opportunities for...-sector firms. The TFC Program seeks to broaden the base of U.S. firms, particularly new-to-market...
Estimation of Flux Between Interacting Nodes on Huge Inter-Firm Networks
NASA Astrophysics Data System (ADS)
Tamura, Koutarou; Miura, Wataru; Takayasu, Misako; Takayasu, Hideki; Kitajima, Satoshi; Goto, Hayato
We analyze Japanese inter-firm network data showing scale-free properties as an example of a real complex network. The data contains information on money flow (annual transaction volume) between about 7000 pairs of firms. We focus on this money-flow data and investigate the correlation between various quantities such as sales or link numbers. We find that the flux from a buyer to a supplier is given by the product of the fractional powers of both sales with different exponents. This result indicates that the principle of detailed balance does not hold in the real transport of money; therefore, random walk type transport models such as PageRank are not suitable.
NASA Astrophysics Data System (ADS)
de Andrés, Javier; Landajo, Manuel; Lorca, Pedro; Labra, Jose; Ordóñez, Patricia
Artificial neural networks have proven to be useful tools for solving financial analysis problems such as financial distress prediction and audit risk assessment. In this paper we focus on the performance of robust (least absolute deviation-based) neural networks on measuring liquidity of firms. The problem of learning the bivariate relationship between the components (namely, current liabilities and current assets) of the so-called current ratio is analyzed, and the predictive performance of several modelling paradigms (namely, linear and log-linear regressions, classical ratios and neural networks) is compared. An empirical analysis is conducted on a representative data base from the Spanish economy. Results indicate that classical ratio models are largely inadequate as a realistic description of the studied relationship, especially when used for predictive purposes. In a number of cases, especially when the analyzed firms are microenterprises, the linear specification is improved by considering the flexible non-linear structures provided by neural networks.
Impact of amylases on biopolymer dynamics during storage of straight-dough wheat bread.
Bosmans, Geertrui M; Lagrain, Bert; Fierens, Ellen; Delcour, Jan A
2013-07-03
When Bacillus stearothermophilus α-amylase (BStA), Pseudomonas saccharophila α-amylase (PSA), or Bacillus subtilis α-amylase (BSuA) was added to a bread recipe to impact bread firming, amylose crystal formation was facilitated, leading to lower initial crumb resilience. Bread loaves that best retained their quality were those obtained when BStA was used. The enzyme hindered formation of an extended starch network, resulting in less water immobilization and smaller changes in crumb firmness and resilience. BSuA led to extensive degradation of the starch network during bread storage with release of immobilized water, eventually resulting in partial structure collapse and poor crumb resilience. The most important effect of PSA was an increased bread volume, resulting in smaller changes in crumb firmness and resilience. A negative linear relation was found between NMR proton mobilities of water and biopolymers in the crumb and crumb firmness. The slope of that relation gave an indication of the strength of the starch network.
The community structure of the global corporate network.
Vitali, Stefania; Battiston, Stefano
2014-01-01
We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the meta-network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide a quantitative assessment of the financial sector role in connecting the global economy.
The Community Structure of the Global Corporate Network
Vitali, Stefania; Battiston, Stefano
2014-01-01
We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the meta-network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide a quantitative assessment of the financial sector role in connecting the global economy. PMID:25126722
Strategic Delay and Information Exchange in Endogenous Social Networks
2010-09-01
suppose that firm 1 experiments while firm 2 delays and copies a successful innovation by firm 1. In this case, the social surplus is equal to 2pH 2 + (1...suppose that there has been an innovation and the second firm has probability of success equal to p. In this case, social surplus is equal to 2112 if...there is copying, and it is equal to HI1 + pli if the second firm is forced to experiment. This implies that to maximize ex post social welfare
Interdependent Risk and Cyber Security: An Analysis of Security Investment and Cyber Insurance
ERIC Educational Resources Information Center
Shim, Woohyun
2010-01-01
An increasing number of firms rely on highly interconnected information networks. In such environments, defense against cyber attacks is complicated by residual risks caused by the interdependence of information security decisions of firms. IT security is affected not only by a firm's own management strategies but also by those of others. This…
ERIC Educational Resources Information Center
Bishop, Dan
2011-01-01
Purpose: The purpose of this paper is to examine the ways in which the small firm's external relationships influence its approach to formal training and training providers. Design/methodology/approach: A qualitative approach was adopted, involving semi-structured interviews with senior managers, in 25 small firms in South Wales. These interviews…
Hypercompetitive Environments: An Agent-based model approach
NASA Astrophysics Data System (ADS)
Dias, Manuel; Araújo, Tanya
Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.
Subcommunities and Their Mutual Relationships in a Transaction Network
NASA Astrophysics Data System (ADS)
Iino, T.; Iyetomi, H.
We investigate a Japanese transaction network consisting ofabout 800 thousand firms (nodes) and four million business relations (links) with focus on its modular structure. Communities detected by maximizing modularity often are dominated by firms with common features or behaviors in the network, such as characterized by regions or industry sectors. However, it is well known that the modularity optimization approach has a resolution limit problem, that is, it fails in identifying fine communities buried in large communities. To unfold such hidden structures, we apply the community detection to each of subnetworks formed by isolating those communities from the whole body. Subcommunities thus identified are composed of firms with finer regions, more specified sectors or business affiliations. Also we introduce a new idea of reduced modularity matrix to measure the strength of relations between (sub)communities.
NASA Astrophysics Data System (ADS)
Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo
2015-04-01
This paper considers stock prices in the Korean stock market during the 2008 global financial crisis by focusing on three time periods: before, during, and after the crisis. Complex networks are extracted from cross-correlation coefficients between the normalized logarithmic return of the stock price time series of firms. The minimal spanning trees (MSTs) and the hierarchical network (HN) are generated from cross-correlation coefficients. Before and after the crisis, securities firms are located at the center of the MST. During the crisis, however, the center of the MST changes to a firm in heavy industry and construction. During the crisis, the MST shrinks in comparison to that before and that after the crisis. This topological change in the MST during the crisis reflects a distinct effect of the global financial crisis. The cophenetic correlation coefficient increases during the crisis, indicating an increase in the hierarchical structure during in this period. When crisis hits the market, firms behave synchronously, and their correlations are higher than those during a normal period.
NASA Astrophysics Data System (ADS)
Hou, Rui; Wu, Jiawen; Du, Helen S.
2017-03-01
To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.
AGENT-BASED MODELING OF INDUSTRIAL ECOSYSTEMS
The objectives of this research are to investigate behavioral and organizational questions associated with environmental regulation of firms, and to test specifically whether a bottom-up approach that highlights principal-agent problems offers new insights and empirical validi...
Generalised Sandpile Dynamics on Artificial and Real-World Directed Networks
Zachariou, Nicky; Expert, Paul; Takayasu, Misako; Christensen, Kim
2015-01-01
The main finding of this paper is a novel avalanche-size exponent τ ≈ 1.87 when the generalised sandpile dynamics evolves on the real-world Japanese inter-firm network. The topology of this network is non-layered and directed, displaying the typical bow tie structure found in real-world directed networks, with cycles and triangles. We show that one can move from a strictly layered regular lattice to a more fluid structure of the inter-firm network in a few simple steps. Relaxing the regular lattice structure by introducing an interlayer distribution for the interactions, forces the scaling exponent of the avalanche-size probability density function τ out of the two-dimensional directed sandpile universality class τ = 4/3, into the mean field universality class τ = 3/2. Numerical investigation shows that these two classes are the only that exist on the directed sandpile, regardless of the underlying topology, as long as it is strictly layered. Randomly adding a small proportion of links connecting non adjacent layers in an otherwise layered network takes the system out of the mean field regime to produce non-trivial avalanche-size probability density function. Although these do not display proper scaling, they closely reproduce the behaviour observed on the Japanese inter-firm network. PMID:26606143
Generalised Sandpile Dynamics on Artificial and Real-World Directed Networks.
Zachariou, Nicky; Expert, Paul; Takayasu, Misako; Christensen, Kim
2015-01-01
The main finding of this paper is a novel avalanche-size exponent τ ≈ 1.87 when the generalised sandpile dynamics evolves on the real-world Japanese inter-firm network. The topology of this network is non-layered and directed, displaying the typical bow tie structure found in real-world directed networks, with cycles and triangles. We show that one can move from a strictly layered regular lattice to a more fluid structure of the inter-firm network in a few simple steps. Relaxing the regular lattice structure by introducing an interlayer distribution for the interactions, forces the scaling exponent of the avalanche-size probability density function τ out of the two-dimensional directed sandpile universality class τ = 4/3, into the mean field universality class τ = 3/2. Numerical investigation shows that these two classes are the only that exist on the directed sandpile, regardless of the underlying topology, as long as it is strictly layered. Randomly adding a small proportion of links connecting non adjacent layers in an otherwise layered network takes the system out of the mean field regime to produce non-trivial avalanche-size probability density function. Although these do not display proper scaling, they closely reproduce the behaviour observed on the Japanese inter-firm network.
Production, depreciation and the size distribution of firms
NASA Astrophysics Data System (ADS)
Ma, Qi; Chen, Yongwang; Tong, Hui; Di, Zengru
2008-05-01
Many empirical researches indicate that firm size distributions in different industries or countries exhibit some similar characters. Among them the fact that many firm size distributions obey power-law especially for the upper end has been mostly discussed. Here we present an agent-based model to describe the evolution of manufacturing firms. Some basic economic behaviors are taken into account, which are production with decreasing marginal returns, preferential allocation of investments, and stochastic depreciation. The model gives a steady size distribution of firms which obey power-law. The effect of parameters on the power exponent is analyzed. The theoretical results are given based on both the Fokker-Planck equation and the Kesten process. They are well consistent with the numerical results.
Abimbola, Seye; Ogunsina, Kemi; Charles-Okoli, Augustina N; Negin, Joel; Martiniuk, Alexandra L; Jan, Stephen
2016-12-01
One of the consequences of ineffective governments is that they leave space for unlicensed and unregulated informal providers without formal training to deliver a large proportion of health services. Without institutions that facilitate appropriate health care transactions, patients tend to navigate health care markets from one inappropriate provider to another, receiving sub-optimal care, before they find appropriate providers; all the while incurring personal transaction costs. But the top-down interventions to address this barrier to accessing care are hampered by weak governments, as informal providers are entrenched in communities. To explore the role that communities could play in limiting informal providers, we applied the transaction costs theory of the firm which predicts that economic agents tend to organise production within firms when the costs of coordinating exchange through the market are greater than within a firm. In a realist analysis of qualitative data from Nigeria, we found that community health committees sometimes seek to limit informal providers in a manner that is consistent with the transaction costs theory of the firm. The committees deal not through legal sanction but by subtle influence and persuasion in a slow and faltering process of institutional change, leveraging the authority and resources available within their community, and from governments and NGOs. First, they provide information to reduce the market share controlled by informal providers, and then regulation to keep informal providers at bay while making the formal provider more competitive. When these efforts are ineffective or insufficient, committees are faced with a "make-or-buy" decision. The "make" decision involves coordination to co-produce formal health services and facilitate referrals from informal to formal providers. What sometimes results is a quasi-firm-informal and formal providers are networked in a single but loose production unit. These findings suggest that efforts to limit informal providers should seek to, among other things, augment existing community responses.
Business cycles’ correlation and systemic risk of the Japanese supplier-customer network
Chakraborty, Abhijit; Inoue, Hiroyasu; Fujiwara, Yoshi
2017-01-01
This work aims to study and explain the business cycle correlations of the Japanese production network. We consider the supplier-customer network, which is a directed network representing the trading links between Japanese firms (links from suppliers to customers). The community structure of this network is determined by applying the Infomap algorithm. Each community is defined by its GDP and its associated business cycle. Business cycle correlations between communities are estimated based on copula theory. Then, based on firms’ attributes and network topology, these correlations are explained through linear econometric models. The results show strong evidence of business cycle correlations in the Japanese production network. A significant systemic risk is found for high negative or positive shocks. These correlations are explained mainly by the sector and by geographic similarities. Moreover, our results highlight the higher vulnerability of small communities and small firms, which is explained by the disassortative mixing of the production network. PMID:29059233
DOT National Transportation Integrated Search
2012-01-01
Despite the steady growth and the introduction of "set-aside" programs/Affirmative Actions, minority owned firms often faced stiff business challenges. These challenges include a lack of business networking opportunities, limited financial resources,...
NASA Astrophysics Data System (ADS)
Iubatti, Daniela; Masciarelli, Francesca; Simboli, Alberto
This chapter aims to explore how the information-processing capabilities that emerge from a network structure affect the diffusion of innovation in a multidivisional organization. In particular, this study analyzes the role of firm investments in ICT to facilitate communication and knowledge diffusion. Using a qualitative approach, we investigate the behavior of an Italian multinational firm, Engineering S.p.A., analyzing our data using a content analysis procedure. Our results show the limited role of ICT in favoring knowledge exchange both inside and outside the firm's divisions: traditional communication patterns are generally preferred over the use of technologies for information sharing. Additionally, we find that key individuals who play a central role in the firm's communication network are unable to use ICTs for knowledge transfer. We conclude that this is the result of a strategic decision to keep top management practically unchanged since the firm was established. Therefore, key individuals act as filters to knowledge flows. Knowledge, in particular tacit knowledge, is transferred from key individuals to other actors through face-to-face contacts, thereby creating a diseconomy for the organization.
Scarselli, Alberto
2011-01-01
The recording of occupational exposure to carcinogens is a fundamental step in order to assess exposure risk factors in workplaces. The aim of this paper is to describe the characteristics of the Italian register of occupational exposures to carcinogen agents (SIREP). The core data collected in the system are: firm characteristics, worker demographics, and exposure information. Statistical descriptive analyses were performed by economic activity sector, carcinogen agent and geographic location. Currently, the information recorded regard: 12,300 firms, 130,000 workers, and 250,000 exposures. The SIREP database has been set up in order to assess, control and reduce the carcinogen risk at workplace.
1982-02-01
Figure 5 we depict two simple special cases to illus- trate "Increasing returns to coalition size" where Y[S] depends only on the number of agents in S...for the case where the nuber of types Is greater than one . 29 catch che fundamental nonsymmatry between a firm on existence and a firm- in-being, or...economy is given in terms of individuals, goods, preferences and production sets. Oligopoly theory, partial equilibrium theory and the study of game
Extending the User’s Reach. Responsive Networking for Integrated Military Operations
2006-02-01
why customers within DOD increasingly bypass “the system,” and why leading IT firms stay out of the defense market. These anomalies will become...processes, lack the perspective, ability, and incentive to meet joint C4 needs. Those who control money are network providers, not customers ; and they do...should seek to attract IT firms. This requires reform of the Federal Acquisition Regulation as it applies to joint C4, not work-arounds and waivers
ERIC Educational Resources Information Center
Toner, Phillip; Marceau, Jane; Hall, Richard; Considine, Gillian
2004-01-01
Australia's competitive success with innovation-based products and services is an influential factor to its long-term prosperity. This study examines the role of vocational education and training (VET) and occupations in innovative industries and firms. The authors find VET is vital to developing knowledge and practical skills across a broad range…
Shared vision promotes family firm performance.
Neff, John E
2015-01-01
A clear picture of the influential drivers of private family firm performance has proven to be an elusive target. The unique characteristics of private family owned firms necessitate a broader, non-financial approach to reveal firm performance drivers. This research study sought to specify and evaluate the themes that distinguish successful family firms from less successful family firms. In addition, this study explored the possibility that these themes collectively form an effective organizational culture that improves longer-term firm performance. At an organizational level of analysis, research findings identified four significant variables: Shared Vision (PNS), Role Clarity (RCL), Confidence in Management (CON), and Professional Networking (OLN) that positively impacted family firm financial performance. Shared Vision exhibited the strongest positive influence among the significant factors. In addition, Family Functionality (APGAR), the functional integrity of the family itself, exhibited a significant supporting role. Taken together, the variables collectively represent an effective family business culture (EFBC) that positively impacted the long-term financial sustainability of family owned firms. The index of effective family business culture also exhibited potential as a predictive non-financial model of family firm performance.
Shared vision promotes family firm performance
Neff, John E.
2015-01-01
A clear picture of the influential drivers of private family firm performance has proven to be an elusive target. The unique characteristics of private family owned firms necessitate a broader, non-financial approach to reveal firm performance drivers. This research study sought to specify and evaluate the themes that distinguish successful family firms from less successful family firms. In addition, this study explored the possibility that these themes collectively form an effective organizational culture that improves longer-term firm performance. At an organizational level of analysis, research findings identified four significant variables: Shared Vision (PNS), Role Clarity (RCL), Confidence in Management (CON), and Professional Networking (OLN) that positively impacted family firm financial performance. Shared Vision exhibited the strongest positive influence among the significant factors. In addition, Family Functionality (APGAR), the functional integrity of the family itself, exhibited a significant supporting role. Taken together, the variables collectively represent an effective family business culture (EFBC) that positively impacted the long-term financial sustainability of family owned firms. The index of effective family business culture also exhibited potential as a predictive non-financial model of family firm performance. PMID:26042075
Motif formation and industry specific topologies in the Japanese business firm network
NASA Astrophysics Data System (ADS)
Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako
2017-05-01
Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.
Micro-foundations for macroeconomics: New set-up based on statistical physics
NASA Astrophysics Data System (ADS)
Yoshikawa, Hiroshi
2016-12-01
Modern macroeconomics is built on "micro foundations." Namely, optimization of micro agent such as consumer and firm is explicitly analyzed in model. Toward this goal, standard model presumes "the representative" consumer/firm, and analyzes its behavior in detail. However, the macroeconomy consists of 107 consumers and 106 firms. For the purpose of analyzing such macro system, it is meaningless to pursue the micro behavior in detail. In this respect, there is no essential difference between economics and physics. The method of statistical physics can be usefully applied to the macroeconomy, and provides Keynesian economics with correct micro-foundations.
NASA Astrophysics Data System (ADS)
Xie, Xuemei
Based on a survey to 1206 Chinese firms, this paper empirically explores the factors impacting cooperative innovation effect of firms, and seeks to explore the relationship between cooperative innovation effect (CIE) and innovation performance using the technique of Structural Equation Modeling (SEM). The study finds there are significant positive relationships between basic sustaining factors, factors of government and policy, factors of cooperation mechanism and social network, and cooperative innovation effect. However, the result reveals that factors of government and policy demonstrate little impact on the CIE of firms compared with other factors. It is hoped that the findings can pave the way for future studies in improving cooperative innovation capacity for firms in emerging countries.
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.
Internal Capabilities, External Network Position, and Knowledge Creation
ERIC Educational Resources Information Center
Liao, Yin-Chi
2010-01-01
Despite the general consensus on the importance of interfirm networks, there is an ongoing debate centering on which type of network structure is most beneficial to firm performance. While spanning structural holes--a network position with disconnected partners--is argued to be advantageous in terms of providing access to diverse knowledge,…
Optimal Software Strategies in the Presence of Network Externalities
ERIC Educational Resources Information Center
Liu, Yipeng
2009-01-01
Network externalities or alternatively termed network effects are pervasive in computer software markets. While software vendors consider pricing strategies, they must also take into account the impact of network externalities on their sales. My main interest in this research is to describe a firm's strategies and behaviors in the presence of…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-13
..., Inc., Networking and Multimedia Group (``NMG'') Excluding the Multimedia Applications Division..., Inc., Networking and Multimedia Group (``NMG''), excluding the Multimedia Applications Division... certification for workers of the subject firm. The workers are engaged in internal design and engineering...
Mani, Dalhia; Moody, James
2014-01-01
A central theme of economic sociology has been to highlight the complexity and diversity of real world markets, but many network models of economic social structure ignore this feature and rely instead on stylized one-dimensional characterizations. Here, the authors return to the basic insight of structural diversity in economic sociology. Using the Indian interorganizational ownership network as their case, they discover a composite—or “hybrid”—model of economic networks that combines elements of prior stylized models. The network contains a disconnected periphery conforming closely to a “transactional” model; a semiperiphery characterized by small, dense clusters with sporadic links, as predicted in “small-world” models; and finally a nested core composed of clusters connected via multiple independent paths. The authors then show how a firm’s position within the mesolevel structure is associated with demographic features such as age and industry and differences in the extent to which firms engage in multiplex and high-value exchanges. PMID:25418990
Loepfe, Lasse; Cabrales, Antonio; Sánchez, Angel
2013-01-01
The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are "too big to fail". Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweenness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes.
13 CFR 107.50 - Definition of terms.
Code of Federal Regulations, 2010 CFR
2010-01-01
... otherwise, are under the Control of one group or Person. Two or more Licensees are presumed to be under... banking firm acceptable to SBA stating that the non-rated debt instrument is equivalent in risk to the..., employee or agent of a Corporate Licensee; (ii) A Control Person, employee or agent of a Partnership...
Chen, Xiao-Ping; Liu, Dong; Portnoy, Rebecca
2012-01-01
Adopting a multilevel theoretical framework, the authors examined how motivational cultural intelligence influences individual cultural sales--the number of housing transactions occurring between people of different cultural origins. Data from 305 real estate agents employed at 26 real estate firms in the United States demonstrated that an individual's motivational cultural intelligence is positively related to his or her cultural sales. This positive relationship is enhanced by the firm's motivational cultural intelligence and diversity climate. The authors discuss the theoretical and practical implications of their findings in a workplace context that involves cross-cultural interpersonal interactions.
Applying commodity chain analysis to changing modes of alcohol supply in a developing country.
Jernigan, D H
2000-12-01
Development sociology has used global commodity chains as one way of analyzing the dynamics of power and profit-taking in globalized production networks made up of multiple firms and occurring in multiple national settings. A substantial portion of the alcohol supply in developing countries is now produced through such production networks. Particularly in the beer and spirits trade, a small number of transnational firms control networks of local producers, importers, advertisers and distributors. These networks serve to embed transnational or transnationally backed brands in the local culture, using the tools of market research, product design and marketing to influence local drinking practices. Case materials from Malaysia's beer industry help to illustrate how the transnational firms dominate in those links of the commodity chain in which monopoly or oligopoly control is most likely to be found: the design/recipe and marketing/advertising nodes. Their control of the commodity chains and extraction of monopoly or oligopoly profits from them places substantial resources and influence over drinking settings and practices in foreign hands. The impact of this influence on state efficacy and autonomy in setting alcohol policy is an important subject for future research on the creation and implementation of effective alcohol policies in developing societies.
Simulating Nutritional Awareness and Action in Military Populations
1981-04-01
shortening because it resists auto oxidation and will have a longer shelf life. The cookies , chips, or dairy creamer made with such fat may have a...Formulated products include bread, which dates from the days of the Pharaohs, and more recently ready-to-bake oven rolls or box cake mixes or cookie ...pickling agents 6. Dough strengthened 7. Drying agents 8. Emuisifiers, emulsifier salts ’ 9. Enzymes 10. Firming agents 11. Flavor enhancers 12
A Novel Network Attack Audit System based on Multi-Agent Technology
NASA Astrophysics Data System (ADS)
Jianping, Wang; Min, Chen; Xianwen, Wu
A network attack audit system which includes network attack audit Agent, host audit Agent and management control center audit Agent is proposed. And the improved multi-agent technology is carried out in the network attack audit Agent which has achieved satisfactory audit results. The audit system in terms of network attack is just in-depth, and with the function improvement of network attack audit Agent, different attack will be better analyzed and audit. In addition, the management control center Agent should manage and analyze audit results from AA (or HA) and audit data on time. And the history files of network packets and host log data should also be audit to find deeper violations that cannot be found in real time.
Loepfe, Lasse; Cabrales, Antonio; Sánchez, Angel
2013-01-01
The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are “too big to fail”. Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweeness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes. PMID:24147017
Using Action Research and Action Learning for Entrepreneurial Network Capability Development
ERIC Educational Resources Information Center
McGrath, Helen; O'Toole, Thomas
2016-01-01
This paper applies an action research (AR) design and action learning (AL) approach to network capability development in an entrepreneurial context. Recent research suggests that networks are a viable strategy for the entrepreneurial firm to overcome the liabilities associated with newness and smallness. However, a gap emerges as few, if any,…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-25
... Network A and Network B data feeds. Consistent with current practice, within each of a firm's billable... fee schedules by compressing the current 14-tier Network A device rate schedule into four tiers, by... products, unprecedented levels of trading, internationalization and developments in portfolio analysis and...
NASA Astrophysics Data System (ADS)
Huseyin Turan, Hasan; Kasap, Nihat; Savran, Huseyin
2014-03-01
Nowadays, every firm uses telecommunication networks in different amounts and ways in order to complete their daily operations. In this article, we investigate an optimisation problem that a firm faces when acquiring network capacity from a market in which there exist several network providers offering different pricing and quality of service (QoS) schemes. The QoS level guaranteed by network providers and the minimum quality level of service, which is needed for accomplishing the operations are denoted as fuzzy numbers in order to handle the non-deterministic nature of the telecommunication network environment. Interestingly, the mathematical formulation of the aforementioned problem leads to the special case of a well-known two-dimensional bin packing problem, which is famous for its computational complexity. We propose two different heuristic solution procedures that have the capability of solving the resulting nonlinear mixed integer programming model with fuzzy constraints. In conclusion, the efficiency of each algorithm is tested in several test instances to demonstrate the applicability of the methodology.
A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks.
Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il
2017-11-09
Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new ( m , k )-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the ( m , k )-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured ( m , k )-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption.
Mergers, networking, and vertical integration: managed care and investor-owned hospitals.
Brown, M
1996-01-01
This article links the forces of managed care and investor-owned firms as major factors driving the industry toward consolidation into vertically integrated, merged firms, often financed with investor capital. This relentless pressure to build regional systems of health services has transformed the industry from a charitable, community orientation to one of business, market shares, and profits.
Examining the articulation of innovativeness in co-creative firms: a neural network approach
NASA Astrophysics Data System (ADS)
di Tollo, Giacomo; Tanev, Stoyan
2010-10-01
Value co-creation is an emerging marketing and innovation paradigm describing a broader opening of the firm to its customers by providing them with the opportunity to become active participants in the design and development of personalized products, services and experiences. The aim of the present contribution is to provide preliminary results from a research project focusing on the relationship between value co-creation and the perception of innovation in technology-driven firms. The data was collected in a previous study using web search techniques and factor analysis to identify the key co-creation components and the frequency of firms' online comments about their new products, processes and services. The present work focuses on using an Artificial Neural Network (ANN) approach to understand if the extent of value co-creation activities can be thought of as an indicator of the perception of innovation. The preliminary simulation results indicate the existence of such relationship. The ANN approach does not suggest a specific model but the relationship that was found out between the forecasted values of the perception of innovation and its actual values clearly points in this direction.
Examining the articulation of innovativeness in co-creative firms: a neural network approach
NASA Astrophysics Data System (ADS)
di Tollo, Giacomo; Tanev, Stoyan
2011-03-01
Value co-creation is an emerging marketing and innovation paradigm describing a broader opening of the firm to its customers by providing them with the opportunity to become active participants in the design and development of personalized products, services and experiences. The aim of the present contribution is to provide preliminary results from a research project focusing on the relationship between value co-creation and the perception of innovation in technology-driven firms. The data was collected in a previous study using web search techniques and factor analysis to identify the key co-creation components and the frequency of firms' online comments about their new products, processes and services. The present work focuses on using an Artificial Neural Network (ANN) approach to understand if the extent of value co-creation activities can be thought of as an indicator of the perception of innovation. The preliminary simulation results indicate the existence of such relationship. The ANN approach does not suggest a specific model but the relationship that was found out between the forecasted values of the perception of innovation and its actual values clearly points in this direction.
Determinants of Network News Coverage of the Oil Industry during the Late 1970s.
ERIC Educational Resources Information Center
Erfle, Stephen; McMillan, Henry
1989-01-01
Examines which firms and products best predict media coverage of the oil industry. Reports that price variations in testing oil and gasoline correlate with the extent of news coverage provided by network television. (MM)
An Evolutionary Complex Systems Decision-Support Tool for the Management of Operations
NASA Astrophysics Data System (ADS)
Baldwin, J. S.; Allen, P. M.; Ridgway, K.
2011-12-01
This research aimed to add both to the development of complex systems thinking in the subject area of Operations and Production Management and to the limited number of applications of computational models and simulations from the science of complex systems. The latter potentially offer helpful decision-support tools for operations and production managers. A mechanical engineering firm was used as a case study where a combined qualitative and quantitative methodological approach was employed to extract the required data from four senior managers. Company performance measures as well as firm technologies, practices and policies, and their relation and interaction with one another, were elicited. The data were subjected to an evolutionary complex systems model resulting in a series of simulations. The findings included both reassuring and some unexpected results. The simulation based on the CEO's opinions led the most cohesive and synergistic collection of practices describing the firm, closely followed by the Marketing and R&D Managers. The Manufacturing Manager's responses led to the most extreme evolutionary trajectory where the integrity of the entire firm came into question particularly when considering how employees were utilised. By drawing directly from the opinions and views of managers rather than from logical 'if-then' rules and averaged mathematical representations of agents that characterise agent-based and other self-organisational models, this work builds on previous applications by capturing a micro-level description of diversity and a learning effect that has been problematical not only in terms of theory but also in application. This approach can be used as a decision-support tool for operations and other managers providing a forum with which to explore a) the strengths, weaknesses and consequences of different decision-making capacities within the firm; b) the introduction of new manufacturing technologies, practices and policies; and, c) the different evolutionary trajectories that a firm can take.
Dimensions of Entrepreneurial Success: A Multilevel Study on Stakeholders of Micro-Enterprises
Razmus, Wiktor; Laguna, Mariola
2018-01-01
The study provides an insight into the indicators and dimensions of entrepreneurial success as evaluated from the external stockholders’ perspective. As each firm is embedded in a network of relations with stakeholders (business partners), understanding how they evaluate entrepreneurial success is important. The initial qualitative study in the form of in-depth interviews allowed us to identify the indicators of entrepreneurial success that are identified by external stakeholders of micro-firms. In the quantitative study on 475 stakeholders of 57 micro-firms, we identified the dimensions of entrepreneurial success. Using a multilevel approach, we found six dimensions of entrepreneurial success at the individual stakeholder level and four dimensions at the firm level. The results show that stakeholders perceive entrepreneurial success in terms of many dimensions, not focusing solely on economic indicators. This knowledge may inform micro-firm management and the strategies employed by practitioners supporting entrepreneurs. PMID:29892242
Environmental Concerns, Environmental Policy and Green Investment.
Gao, Xuexian; Zheng, Haidong
2017-12-13
Environmental regulators often use environmental policy to induce green investment by firms. However, if an environmental policy fails to exert a long-run effect on regulating the economic agents' behavior, it may be more reasonable to think of the firm as the leader in the game, since the investment in green technology is usually a strategic decision. In this paper, we consider a three-stage Stackelberg game to address the interaction between a profit-maximizing firm (Stackelberg leader) facing emission-dependent demand, and the environmental regulator (Stackelberg follower). The firm decides on the green technology level in the first stage of the game based on its understanding of the regulator's profits function, especially an environmental concern that is introduced as an exogenous variable. In the current research, we show that high levels of the regulator's environmental concerns do not necessarily lead to the choice of green technology by the firm, and green investment level depends on the combined effects of the market and operational factors for a given level of the regulator's environmental concerns. The result also shows that increasing environmental awareness amongst the consumers is an effective way to drive the firm's green investment.
Adaptive capacity of geographical clusters: Complexity science and network theory approach
NASA Astrophysics Data System (ADS)
Albino, Vito; Carbonara, Nunzia; Giannoccaro, Ilaria
This paper deals with the adaptive capacity of geographical clusters (GCs), that is a relevant topic in the literature. To address this topic, GC is considered as a complex adaptive system (CAS). Three theoretical propositions concerning the GC adaptive capacity are formulated by using complexity theory. First, we identify three main properties of CAS s that affect the adaptive capacity, namely the interconnectivity, the heterogeneity, and the level of control, and define how the value of these properties influence the adaptive capacity. Then, we associate these properties with specific GC characteristics so obtaining the key conditions of GCs that give them the adaptive capacity so assuring their competitive advantage. To test these theoretical propositions, a case study on two real GCs is carried out. The considered GCs are modeled as networks where firms are nodes and inter-firms relationships are links. Heterogeneity, interconnectivity, and level of control are considered as network properties and thus measured by using the methods of the network theory.
Maintaining Limited-Range Connectivity Among Second-Order Agents
2016-07-07
we consider ad-hoc networks of robotic agents with double integrator dynamics. For such networks, the connectivity maintenance problems are: (i) do...hoc networks of mobile autonomous agents. This loose ter- minology refers to groups of robotic agents with limited mobility and communica- tion...connectivity can be preserved. 3.1. Networks of robotic agents with second-order dynamics and the connectivity maintenance problem. We begin by
A Tree Based Broadcast Scheme for (m, k)-firm Real-Time Stream in Wireless Sensor Networks
Park, HoSung; Kim, Beom-Su; Kim, Kyong Hoon; Shah, Babar; Kim, Ki-Il
2017-01-01
Recently, various unicast routing protocols have been proposed to deliver measured data from the sensor node to the sink node within the predetermined deadline in wireless sensor networks. In parallel with their approaches, some applications demand the specific service, which is based on broadcast to all nodes within the deadline, the feasible real-time traffic model and improvements in energy efficiency. However, current protocols based on either flooding or one-to-one unicast cannot meet the above requirements entirely. Moreover, as far as the authors know, there is no study for the real-time broadcast protocol to support the application-specific traffic model in WSN yet. Based on the above analysis, in this paper, we propose a new (m, k)-firm-based Real-time Broadcast Protocol (FRBP) by constructing a broadcast tree to satisfy the (m, k)-firm, which is applicable to the real-time model in resource-constrained WSNs. The broadcast tree in FRBP is constructed by the distance-based priority scheme, whereas energy efficiency is improved by selecting as few as nodes on a tree possible. To overcome the unstable network environment, the recovery scheme invokes rapid partial tree reconstruction in order to designate another node as the parent on a tree according to the measured (m, k)-firm real-time condition and local states monitoring. Finally, simulation results are given to demonstrate the superiority of FRBP compared to the existing schemes in terms of average deadline missing ratio, average throughput and energy consumption. PMID:29120404
38 CFR 36.4347 - Lender Appraisal Processing Program.
Code of Federal Regulations, 2010 CFR
2010-07-01
...., to the appraisal report must be made in a contrasting color, be clearly legible, and signed and dated... with a real estate firm builder, land developer or escrow agent as a subsidiary division, investment or...
Properties of interaction networks underlying the minority game.
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.
Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei
2014-01-01
Multispectral imaging with 19 wavelengths in the range of 405-970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit.
Globalization in the pharmaceutical industry, Part I.
Casadio Tarabusi, C; Vickery, G
1998-01-01
This report on the pharmaceutical industry will be published in two parts. Part I begins with a summary of the study and its conclusions. The authors then provide an overview of the characteristics of the industry and current trends in its growth and structure: production and consumption, employment, research and development, capital investment, firm and product concentration and product competition, and pricing. A discussion of international trade follows, covering intra- and inter-regional, intra-firm, and intra-industry trade. The report will continue in the next issue of the Journal (Part II) with a look at foreign direct investment, inter-firm networks, and governmental policies.
38 CFR 36.4348 - Servicer Appraisal Processing Program.
Code of Federal Regulations, 2010 CFR
2010-07-01
..., justifications, etc., to the appraisal report must be made in a contrasting color, be clearly legible, and signed... with a real estate firm, builder, land developer or escrow agent as a subsidiary division, or in any...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-29
...-dealers and aggregators such as electronic communications networks. A member firm is able to select any... (`ATSs') and electronic communications networks (`ECNs') that the Commission has also nurtured and... the following methods: Electronic Comments Use the Commission's Internet comment form ( http://www.sec...
Network-Centric Warfare: Implications for Applying the Principles of War
1999-05-17
Noting the competitive advantage that a computer network system completely integrated into a firm’s structure and operations has provided to...businesses, individuals have begun to argue that adoption of this concept by the United States armed forces would produce a comparable, competitive advantage in
77 FR 56669 - Proposed Flood Hazard Determinations
Federal Register 2010, 2011, 2012, 2013, 2014
2012-09-13
...Comments are requested on proposed flood hazard determinations, which may include additions or modifications of any Base Flood Elevation (BFE), base flood depth, Special Flood Hazard Area (SFHA) boundary or zone designation, or regulatory floodway on the Flood Insurance Rate Maps (FIRMs), and where applicable, in the supporting Flood Insurance Study (FIS) reports for the communities listed in the table below. The purpose of this notice is to seek general information and comment regarding the preliminary FIRM, and where applicable, the FIS report that the Federal Emergency Management Agency (FEMA) has provided to the affected communities. The FIRM and FIS report are the basis of the floodplain management measures that the community is required either to adopt or to show evidence of having in effect in order to qualify or remain qualified for participation in the National Flood Insurance Program (NFIP). In addition, the FIRM and FIS report, once effective, will be used by insurance agents and others to calculate appropriate flood insurance premium rates for new buildings and the contents of those buildings.
Network flow of mobile agents enhances the evolution of cooperation
NASA Astrophysics Data System (ADS)
Ichinose, G.; Satotani, Y.; Nagatani, T.
2018-01-01
We study the effect of contingent movement on the persistence of cooperation on complex networks with empty nodes. Each agent plays the Prisoner's Dilemma game with its neighbors and then it either updates the strategy depending on the payoff difference with neighbors or it moves to another empty node if not satisfied with its own payoff. If no neighboring node is empty, each agent stays at the same site. By extensive evolutionary simulations, we show that the medium density of agents enhances cooperation where the network flow of mobile agents is also medium. Moreover, if the movements of agents are more frequent than the strategy updating, cooperation is further promoted. In scale-free networks, the optimal density for cooperation is lower than other networks because agents get stuck at hubs. Our study suggests that keeping a smooth network flow is significant for the persistence of cooperation in ever-changing societies.
Understanding Organizational Agility: A Work-Design Perspective
2008-06-01
NG SDG Proactive Yes Yes Yes Yes Yes Yes N/S N/S N/S Reactive Simultaneity of work design at three levels Yes Supply Chain Network Agility High Table...firm can take effective action to benefit itself and its customers. In analyzing representative supply - chain definitions of agility, the main theme...and Heppard 2000). Third, as effective supply chain management has come to be regarded as major source of competitive advantage for many firms
Quantifying Entrepreneurial Networks: Data Collection in Addis Ababa, Ethiopia
2013-06-10
to meet with the country manager for Schulze Global Investments (SGI), an emerging markets private equity firm. I had been introduced to Ms...member of the mirt team who has developed an interest in photography into a thriving business focusing on assisting firms with marketing and...bring in revenue. The branding business has now taken off and he has four employees and his clients include Pepsi . I also had the opportunity to eat
NASA Astrophysics Data System (ADS)
Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy
2003-03-01
The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.
Code of Federal Regulations, 2013 CFR
2013-01-01
..., leaflet, circular, mailer, book insert, free standing insert, letter, catalogue, poster, chart, billboard... firms, program-length commercial (“infomercial”), the internet, cellular network, or any other medium...
Code of Federal Regulations, 2014 CFR
2014-01-01
..., leaflet, circular, mailer, book insert, free standing insert, letter, catalogue, poster, chart, billboard... firms, program-length commercial (“infomercial”), the internet, cellular network, or any other medium...
Code of Federal Regulations, 2012 CFR
2012-01-01
..., leaflet, circular, mailer, book insert, free standing insert, letter, catalogue, poster, chart, billboard... firms, program-length commercial (“infomercial”), the internet, cellular network, or any other medium...
The Internet and managed care: a new wave of innovation.
Goldsmith, J
2000-01-01
Managed care firms have been under siege in the political system and the marketplace for the past few years. The rise of the Internet has brought into being powerful new electronic tools for automating administrative and financial processes in health insurance. These tools may enable new firms or employers to create custom-designed networks connecting their workers and providers, bypassing health plans altogether. Alternatively, health plans may use these tools to create a new consumer-focused business model. While some disintermediation of managed care plans may occur, the barriers to adoption of Internet tools by established plans are quite low. Network computing may provide important leverage for health plans not only to retain their franchises but also to improve their profitability and customer service.
Sanchís, Elena; Mateos, Milagros; Pérez-Gago, María B
2016-10-01
To prevent enzymatic browning of fresh-cut 'Rojo Brillante' persimmon, different combinations of ascorbic acid (AA) and citric acid (CA) with calcium chloride (CaCl 2 ) were tested in fruit harvested at two maturity stages (MS1 and MS2). Color, firmness, sensory quality, total vitamin C, radical scavenging activity, total phenolic content, and carotenoids were evaluated over nine days of storage at 5 ℃. Antibrowning dips reduced enzymatic browning if compared with the control samples. Selecting fruits with good firmness and the addition of 10 g/l CaCl 2 help prevent loss of firmness of fresh-cut "Rojo Brillante" persimmons treated with acidic solutions as antibrowning agents to control enzymatic browning. The limit of marketability of the persimmon fruit processed at MS1 was significantly reduced by the burst of the disorder known as "flesh browning," and only the samples treated with 10 g/l CA + 10 g/l CaCl 2 maintained a limit of marketability close to seven days. At MS2, all the antibrowning solutions allowed a limit of marketability of seven storage days at 5 ℃. Nutritional quality was not affected by either antibrowning dips or cutting processes, but MS at harvest was. © The Author(s) 2016.
NASA Astrophysics Data System (ADS)
Corkindale, David; Ram, Jiwat; Chen, Howard
2018-02-01
Online communities are a powerful device for collaborative creativity and innovation. Developments in Web 2.0 technologies have given rise to such interactions through firm-hosted online communities (FHOCs) - firm-run online information services that also provide self-help to a community. We devise a model that seeks to explain the factors that encourage people to become members of a FHOC and test the model using structural equation modelling based on data collected from 511 users of a FHOC. The study finds that: (a) an understanding of Perceived Usefulness (PU) plays a mediating role between Behavioural Intention (BI) to adopt FHOC and Trust, as well as Interface design; b) Networking among users has an indirect effect on BI; and c) design of the Interface has a direct influence on BI. A managerial implication is that Networking plays a role in the way supplementary services, including blogs and discussion forums, are perceived. Theoretically, when service quality is decomposed into components such as core services and supplementary services, it also positively influences PU.
Competitive Dynamics on Complex Networks
Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan
2014-01-01
We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition. PMID:25068622
Wealth condensation in a Barabasi-Albert network
NASA Astrophysics Data System (ADS)
Vázquez-Montejo, J.; Huerta-Quintanilla, R.; Rodríguez-Achach, M.
2010-04-01
We study the flow of money among agents in a Barabasi-Albert (BA) scale free network, where each network node represents an agent and money exchange interactions are established through links. The system allows money trade between two agents at a time, betting a fraction f of the poorer’s agent wealth. We also allow for the bet to be biased, giving the poorer agent a winning probability p. In the no network case there is a phase transition involving a relationship between p and f. In the networked case, we also found a condensation interface, however, this is not a complete condensation due to the presence of clusters in the network and its topology. As can be expected, the winner is always a well-connected agent, but we also found that the mean wealth decreases with the agents’ connectivity.
NASA Astrophysics Data System (ADS)
Piao, Chunhui; Han, Xufang; Wu, Harris
2010-08-01
We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.
Western and Eastern Views on Social Networks
ERIC Educational Resources Information Center
Ordonez de Pablos, Patricia
2005-01-01
Purpose: The aim of this paper is to examine social networks from a Western and Eastern view. Design/methodology/approach: The paper uses case study methodology to gather evidence of how world pioneering firms from Asia and Europe measure and report their social connections from a Western perspective. Findings: It examined the basic indicators…
Social Networking Sites as a Learning Tool
ERIC Educational Resources Information Center
Sanchez-Casado, Noelia; Cegarra Navarro, Juan Gabriel; Wensley, Anthony; Tomaseti-Solano, Eva
2016-01-01
Purpose: Over the past few years, social networking sites (SNSs) have become very useful for firms, allowing companies to manage the customer-brand relationships. In this context, SNSs can be considered as a learning tool because of the brand knowledge that customers develop from these relationships. Because of the fact that knowledge in…
75 FR 9578 - Executive-Led Trade Mission to Colombia and Panama; Change to Mission Dates
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-03
..., Panama City, Panama, Market Briefing, Matchmaking appointments, Networking reception. Tuesday, September..., Colombia and Panama City, Panama, September 20-24, 2010, to be led by a senior Commerce official. The... well as market briefings and networking events. The mission will be comprised of U.S. firms...
Knowledge as a Resource--Networks Do Matter: A Study of SME Firms in Rural Illinois.
ERIC Educational Resources Information Center
Solymossy, Emeric
2000-01-01
Networks among people and businesses facilitate the capture and diffusion of technical and organizational knowledge and can be classified by type of knowledge being exchanged. Types include buyer-supplier information, technical problem-solving information, and informal community information. A survey of 141 small and medium-sized enterprises…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-08
... workers of the subject firm. The workers were engaged in the production of Truepoint 5000 XCVR microwave radios and are separately identifiable from workers producing other microwave radios. New information... Division, engaged in employment related to the production of Truepoint 5000 XCVR microwave radios...
Code of Federal Regulations, 2012 CFR
2012-01-01
... REGULATIONS AIRLINE COMPUTER RESERVATIONS SYSTEMS § 255.2 Applicability. This part applies to firms that operate computerized reservations systems for travel agents in the United States, and to the sale in the United States of interstate, overseas, and foreign air transportation through such systems. ...
Code of Federal Regulations, 2013 CFR
2013-01-01
... REGULATIONS AIRLINE COMPUTER RESERVATIONS SYSTEMS § 255.2 Applicability. This part applies to firms that operate computerized reservations systems for travel agents in the United States, and to the sale in the United States of interstate, overseas, and foreign air transportation through such systems. ...
Code of Federal Regulations, 2014 CFR
2014-01-01
... REGULATIONS AIRLINE COMPUTER RESERVATIONS SYSTEMS § 255.2 Applicability. This part applies to firms that operate computerized reservations systems for travel agents in the United States, and to the sale in the United States of interstate, overseas, and foreign air transportation through such systems. ...
Liu, Changhong; Liu, Wei; Lu, Xuzhong; Ma, Fei; Chen, Wei; Yang, Jianbo; Zheng, Lei
2014-01-01
Multispectral imaging with 19 wavelengths in the range of 405–970 nm has been evaluated for nondestructive determination of firmness, total soluble solids (TSS) content and ripeness stage in strawberry fruit. Several analysis approaches, including partial least squares (PLS), support vector machine (SVM) and back propagation neural network (BPNN), were applied to develop theoretical models for predicting the firmness and TSS of intact strawberry fruit. Compared with PLS and SVM, BPNN considerably improved the performance of multispectral imaging for predicting firmness and total soluble solids content with the correlation coefficient (r) of 0.94 and 0.83, SEP of 0.375 and 0.573, and bias of 0.035 and 0.056, respectively. Subsequently, the ability of multispectral imaging technology to classify fruit based on ripeness stage was tested using SVM and principal component analysis-back propagation neural network (PCA-BPNN) models. The higher classification accuracy of 100% was achieved using SVM model. Moreover, the results of all these models demonstrated that the VIS parts of the spectra were the main contributor to the determination of firmness, TSS content estimation and classification of ripeness stage in strawberry fruit. These results suggest that multispectral imaging, together with suitable analysis model, is a promising technology for rapid estimation of quality attributes and classification of ripeness stage in strawberry fruit. PMID:24505317
Network reciprocity by coexisting learning and teaching strategies
NASA Astrophysics Data System (ADS)
Tanimoto, Jun; Brede, Markus; Yamauchi, Atsuo
2012-03-01
We propose a network reciprocity model in which an agent probabilistically adopts learning or teaching strategies. In the learning adaptation mechanism, an agent may copy a neighbor's strategy through Fermi pairwise comparison. The teaching adaptation mechanism involves an agent imposing its strategy on a neighbor. Our simulations reveal that the reciprocity is significantly affected by the frequency with which learning and teaching agents coexist in a network and by the structure of the network itself.
Research and Simulation on Application of the Mobile IP Network
NASA Astrophysics Data System (ADS)
Yibing, Deng; Wei, Hu; Minghui, Li; Feng, Gao; Junyi, Shen
The paper analysed the mobile node, home agent, and foreign agent of mobile IP network firstly, some key technique, such as mobile IP network basical principle, protocol work principle, agent discovery, registration, and IP packet transmission, were discussed. Then a network simulation model was designed, validating the characteristic of mobile IP network, and some advantages, which were brought by mobile network, were testified. Finally, the conclusion is gained: mobile IP network could realize the expectation of consumer that they can communicate with others anywhere.
Joint Services Electronics Program.
1981-04-01
ADMINISTRATIVSAE Contract The Steeri oj~ N00 24. .7 ... 06 Prof, N- BlOe zbergenProf’ I.W* rockettPrfP.E. Caines (term. 7/1/,0)Prof- H. EhrenreichProf. Y.C. Ho Prof...4 111.6 (ii) Stochastic Incentive Problem An incentive problem can be roughly described as follows. Let us consider a firm with two divisions ( agents ...difficulties combined with system dynamics makes the problem very challenging. If there are enough noncooperative agents , we showed that, under relatively mild
75 FR 63805 - Annual Wholesale Trade Survey
Federal Register 2010, 2011, 2012, 2013, 2014
2010-10-18
... Trade Survey AGENCY: Bureau of the Census, Commerce. ACTION: Notice of determination. SUMMARY: The... Wholesale Trade Survey (AWTS). AWTS covers firms with establishments located in the United States and...; and agents, brokers, and electronic markets. Through this survey, the Census Bureau will collect data...
Organization of the secure distributed computing based on multi-agent system
NASA Astrophysics Data System (ADS)
Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera
2018-04-01
Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.
NASA Astrophysics Data System (ADS)
Ahari Mostafavi, Hossein; Mahyar Mirmajlessi, Seyed; Fathollahi, Hadi; Shahbazi, Samira; Mohammad Mirjalili, Seyed
2013-10-01
Effects of gamma irradiation and biocontrol agent (Pseudomonas fluorescens) on the physico-chemical parameters (including moisture, total soluble solids, antioxidant activity, phenolic content and firmness) of cv. Golden Delicious apples were investigated for their ability to avoid the post-harvest blue mold caused by Penicillium expansum during cold storage. Freshly harvested apples were inoculated with P. expansum. Treated fruits were irradiated at doses of 0, 200, 400, 600 and 800 Gy and then inoculated with P. fluorescens suspension. Samples were evaluated at 3 month intervals. The results demonstrated a clear link between antioxidant activity and phenolic content, so that dose range of 200-400 Gy significantly increased phenolic content and antioxidant activity. Effect of P. fluorescens was similar to irradiation at 200 and 400 Gy that could prevent lesion diameter in pathogen-treated apples. As dose and storage time increased firmness decreased but, combination of P. fluorescens as well as irradiation (at 200-400 Gy) could decrease softening apple fruits during storage. In all parameters, P. fluorescens (as biocontrol agent) inhibited P. expansum similar to irradiation at 200-400 Gy. So, integrated treatment of irradiation and biocontrol agent explored the potential dual benefit of low doses (200 and 400 Gy) as a suitable method to sustain physico-chemical quality and conclusively reduce apple fruits losses during post-harvest preservation.
Using Synchronous Boolean Networks to Model Several Phenomena of Collective Behavior
Kochemazov, Stepan; Semenov, Alexander
2014-01-01
In this paper, we propose an approach for modeling and analysis of a number of phenomena of collective behavior. By collectives we mean multi-agent systems that transition from one state to another at discrete moments of time. The behavior of a member of a collective (agent) is called conforming if the opinion of this agent at current time moment conforms to the opinion of some other agents at the previous time moment. We presume that at each moment of time every agent makes a decision by choosing from the set (where 1-decision corresponds to action and 0-decision corresponds to inaction). In our approach we model collective behavior with synchronous Boolean networks. We presume that in a network there can be agents that act at every moment of time. Such agents are called instigators. Also there can be agents that never act. Such agents are called loyalists. Agents that are neither instigators nor loyalists are called simple agents. We study two combinatorial problems. The first problem is to find a disposition of instigators that in several time moments transforms a network from a state where the majority of simple agents are inactive to a state with the majority of active agents. The second problem is to find a disposition of loyalists that returns the network to a state with the majority of inactive agents. Similar problems are studied for networks in which simple agents demonstrate the contrary to conforming behavior that we call anticonforming. We obtained several theoretical results regarding the behavior of collectives of agents with conforming or anticonforming behavior. In computational experiments we solved the described problems for randomly generated networks with several hundred vertices. We reduced corresponding combinatorial problems to the Boolean satisfiability problem (SAT) and used modern SAT solvers to solve the instances obtained. PMID:25526612
Fast Flux Watch: A mechanism for online detection of fast flux networks.
Al-Duwairi, Basheer N; Al-Hammouri, Ahmad T
2014-07-01
Fast flux networks represent a special type of botnets that are used to provide highly available web services to a backend server, which usually hosts malicious content. Detection of fast flux networks continues to be a challenging issue because of the similar behavior between these networks and other legitimate infrastructures, such as CDNs and server farms. This paper proposes Fast Flux Watch (FF-Watch), a mechanism for online detection of fast flux agents. FF-Watch is envisioned to exist as a software agent at leaf routers that connect stub networks to the Internet. The core mechanism of FF-Watch is based on the inherent feature of fast flux networks: flux agents within stub networks take the role of relaying client requests to point-of-sale websites of spam campaigns. The main idea of FF-Watch is to correlate incoming TCP connection requests to flux agents within a stub network with outgoing TCP connection requests from the same agents to the point-of-sale website. Theoretical and traffic trace driven analysis shows that the proposed mechanism can be utilized to efficiently detect fast flux agents within a stub network.
Multi-agent coordination in directed moving neighbourhood random networks
NASA Astrophysics Data System (ADS)
Shang, Yi-Lun
2010-07-01
This paper considers the consensus problem of dynamical multiple agents that communicate via a directed moving neighbourhood random network. Each agent performs random walk on a weighted directed network. Agents interact with each other through random unidirectional information flow when they coincide in the underlying network at a given instant. For such a framework, we present sufficient conditions for almost sure asymptotic consensus. Numerical examples are taken to show the effectiveness of the obtained results.
Oğüt, Hulisi; Raghunathan, Srinivasan; Menon, Nirup
2011-03-01
The correlated nature of security breach risks, the imperfect ability to prove loss from a breach to an insurer, and the inability of insurers and external agents to observe firms' self-protection efforts have posed significant challenges to cyber security risk management. Our analysis finds that a firm invests less than the social optimal levels in self-protection and in insurance when risks are correlated and the ability to prove loss is imperfect. We find that the appropriate social intervention policy to induce a firm to invest at socially optimal levels depends on whether insurers can verify a firm's self-protection levels. If self-protection of a firm is observable to an insurer so that it can design a contract that is contingent on the self-protection level, then self-protection and insurance behave as complements. In this case, a social planner can induce a firm to choose the socially optimal self-protection and insurance levels by offering a subsidy on self-protection. We also find that providing a subsidy on insurance does not provide a similar inducement to a firm. If self-protection of a firm is not observable to an insurer, then self-protection and insurance behave as substitutes. In this case, a social planner should tax the insurance premium to achieve socially optimal results. The results of our analysis hold regardless of whether the insurance market is perfectly competitive or not, implying that solely reforming the currently imperfect insurance market is insufficient to achieve the efficient outcome in cyber security risk management. © 2010 Society for Risk Analysis.
McKelvey, Maureen
2016-01-01
The main contribution of this paper is a theory-based conceptual framework of innovation spaces, and how firms must navigate through them to innovate. The concept of innovation systems - at the regional, sectoral and national levels - have been highly influential. Previous literature developing the concept of innovation systems has stressed the importance of institutions, networks and knowledge bases at the regional, sectoral and national levels. This paper primarily draws upon an evolutionary and Schumpeterian economics perspective, in the following three senses. The conceptualization of 'innnovation spaces' focuses upon how and why firm search for innovations is influenced the opportunities within certain geographical contexts. This means that the firm create opportunities and can span different context, but they are influence by the context in term of the access, flow and co-evolution of ideas, resources, technology, people and knowledge, which help stimulate business innovation in terms of products, process and services. The paper concludes with an agenda for future research and especially the need to focus on globalization as a process of intensifying linkages across the globe.
Globalization in the pharmaceutical industry, Part II.
Casadio Tarabusi, C; Vickery, G
1998-01-01
This is the second of a two-part report on the pharmaceutical industry. Part II begins with a discussion of foreign direct investment and inter-firm networks, which covers international mergers, acquisitions, and minority participation; market shares of foreign-controlled firms; international collaboration agreements (with a special note on agreements in biotechnology); and licensing agreements. The final section of the report covers governmental policies on health and safety regulation, price regulation, industry and technology, trade, foreign investment, protection of intellectual property, and competition.
Model of mobile agents for sexual interactions networks
NASA Astrophysics Data System (ADS)
González, M. C.; Lind, P. G.; Herrmann, H. J.
2006-02-01
We present a novel model to simulate real social networks of complex interactions, based in a system of colliding particles (agents). The network is build by keeping track of the collisions and evolves in time with correlations which emerge due to the mobility of the agents. Therefore, statistical features are a consequence only of local collisions among its individual agents. Agent dynamics is realized by an event-driven algorithm of collisions where energy is gained as opposed to physical systems which have dissipation. The model reproduces empirical data from networks of sexual interactions, not previously obtained with other approaches.
The maintenance of cooperation in multiplex networks with limited and partible resources of agents
NASA Astrophysics Data System (ADS)
Li, Zhaofeng; Shen, Bi; Jiang, Yichuan
2017-02-01
In this paper, we try to explain the maintenance of cooperation in multiplex networks with limited and partible resources of agents: defection brings larger short-term benefit and cooperative agents may become defective because of the unaffordable costs of cooperative behaviors that are performed in multiple layers simultaneously. Recent studies have identified the positive effects of multiple layers on evolutionary cooperation but generally overlook the maximum costs of agents in these synchronous games. By utilizing network effects and designing evolutionary mechanisms, cooperative behaviors become prevailing in public goods games, and agents can allocate personal resources across multiple layers. First, we generalize degree diversity into multiplex networks to improve the prospect for cooperation. Second, to prevent agents allocating all the resources into one layer, a greedy-first mechanism is proposed, in which agents prefer to add additional investments in the higher-payoff layer. It is found that greedy-first agents can perform cooperative behaviors in multiplex networks when one layer is scale-free network and degree differences between conjoint nodes increase. Our work may help to explain the emergence of cooperation in the absence of individual reputation and punishment mechanisms.
32 CFR 552.57 - Authorization to solicit.
Code of Federal Regulations, 2010 CFR
2010-07-01
... specific appointment must be made with the individual and must be conducted in family quarters or in other..., whether the agent is employed by a reputable firm. (b) Certain companies seeking solicitation privileges on military installations may arrange personal demonstrations of their products at social gatherings...
Coevolution in management fashion: an agent-based model of consultant-driven innovation.
Strang, David; David, Robert J; Akhlaghpour, Saeed
2014-07-01
The rise of management consultancy has been accompanied by increasingly marked faddish cycles in management techniques, but the mechanisms that underlie this relationship are not well understood. The authors develop a simple agent-based framework that models innovation adoption and abandonment on both the supply and demand sides. In opposition to conceptions of consultants as rhetorical wizards who engineer waves of management fashion, firms and consultants are treated as boundedly rational actors who chase the secrets of success by mimicking their highest-performing peers. Computational experiments demonstrate that consultant-driven versions of this dynamic in which the outcomes of firms are strongly conditioned by their choice of consultant are robustly faddish. The invasion of boom markets by low-quality consultants undercuts popular innovations while simultaneously restarting the fashion cycle by prompting the flight of high-quality consultants into less densely occupied niches. Computational experiments also indicate conditions involving consultant mobility, aspiration levels, mimic probabilities, and client-provider matching that attenuate faddishness.
Agent of whirling disease meets orphan worm: phylogenomic analyses firmly place Myxozoa in Cnidaria.
Nesnidal, Maximilian P; Helmkampf, Martin; Bruchhaus, Iris; El-Matbouli, Mansour; Hausdorf, Bernhard
2013-01-01
Myxozoa are microscopic obligate endoparasites with complex live cycles. Representatives are Myxobolus cerebralis, the causative agent of whirling disease in salmonids, and the enigmatic "orphan worm" Buddenbrockia plumatellae parasitizing in Bryozoa. Originally, Myxozoa were classified as protists, but later several metazoan characteristics were reported. However, their phylogenetic relationships remained doubtful. Some molecular phylogenetic analyses placed them as sister group to or even within Bilateria, whereas the possession of polar capsules that are similar to nematocysts of Cnidaria and of minicollagen genes suggest a close relationship between Myxozoa and Cnidaria. EST data of Buddenbrockia also indicated a cnidarian origin of Myxozoa, but were not sufficient to reject a closer relationship to bilaterians. Phylogenomic analyses of new genomic sequences of Myxobolus cerebralis firmly place Myxozoa as sister group to Medusozoa within Cnidaria. Based on the new dataset, the alternative hypothesis that Myxozoa form a clade with Bilateria can be rejected using topology tests. Sensitivity analyses indicate that this result is not affected by long branch attraction artifacts or compositional bias.
Attitude Survey of Civilian Housing Residents, Hawaii 1986.
1987-05-01
occupied housing, with the family housing with respect to their housing average value of a single family house at management and related support...Don’t know 11% Rent through agent or 4% Through a friend newspaper, friend or family or family member to manage 64% Through an agent 2% Rent through...HRO, friend or 9% Other family to manage it 54% Turn it over to a property management firm Over half (54%) of the home owners re- 18% Other sponding
NASA Astrophysics Data System (ADS)
Kodama, Yu; Hamagami, Tomoki
Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.
a Model for Brand Competition Within a Social Network
NASA Astrophysics Data System (ADS)
Huerta-Quintanilla, R.; Canto-Lugo, E.; Rodríguez-Achach, M.
An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.
Resilient distributed control in the presence of misbehaving agents in networked control systems.
Zeng, Wente; Chow, Mo-Yuen
2014-11-01
In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.
How the ownership structures cause epidemics in financial markets: A network-based simulation model
NASA Astrophysics Data System (ADS)
Dastkhan, Hossein; Gharneh, Naser Shams
2018-02-01
Analysis of systemic risks and contagions is one of the main challenges of policy makers and researchers in the recent years. Network theory is introduced as a main approach in the modeling and simulation of financial and economic systems. In this paper, a simulation model is introduced based on the ownership network to analyze the contagion and systemic risk events. For this purpose, different network structures with different values for parameters are considered to investigate the stability of the financial system in the presence of different kinds of idiosyncratic and aggregate shocks. The considered network structures include Erdos-Renyi, core-periphery, segregated and power-law networks. Moreover, the results of the proposed model are also calculated for a real ownership network. The results show that the network structure has a significant effect on the probability and the extent of contagion in the financial systems. For each network structure, various values for the parameters results in remarkable differences in the systemic risk measures. The results of real case show that the proposed model is appropriate in the analysis of systemic risk and contagion in financial markets, identification of systemically important firms and estimation of market loss when the initial failures occur. This paper suggests a new direction in the modeling of contagion in the financial markets, in particular that the effects of new kinds of financial exposure are clarified. This paper's idea and analytical results may also be useful for the financial policy makers, portfolio managers and the firms to conduct their investment in the right direction.
24 CFR 30.45 - Multifamily and section 202 or 811 mortgagors.
Code of Federal Regulations, 2012 CFR
2012-04-01
... only: (1) Agent employed to manage the property that has an identity of interest and identity of... individual corporation; company; association; partnership; authority; firm; society; trust; state, local government or agency thereof; or any other organization or group of people. (4) Multifamily property...
24 CFR 30.45 - Multifamily and section 202 or 811 mortgagors.
Code of Federal Regulations, 2014 CFR
2014-04-01
... only: (1) Agent employed to manage the property that has an identity of interest and identity of... individual corporation; company; association; partnership; authority; firm; society; trust; state, local government or agency thereof; or any other organization or group of people. (4) Multifamily property...
24 CFR 30.45 - Multifamily and section 202 or 811 mortgagors.
Code of Federal Regulations, 2011 CFR
2011-04-01
... only: (1) Agent employed to manage the property that has an identity of interest and identity of... individual corporation; company; association; partnership; authority; firm; society; trust; state, local government or agency thereof; or any other organization or group of people. (4) Multifamily property...
24 CFR 30.45 - Multifamily and section 202 or 811 mortgagors.
Code of Federal Regulations, 2013 CFR
2013-04-01
... only: (1) Agent employed to manage the property that has an identity of interest and identity of... individual corporation; company; association; partnership; authority; firm; society; trust; state, local government or agency thereof; or any other organization or group of people. (4) Multifamily property...
24 CFR 30.45 - Multifamily and section 202 or 811 mortgagors.
Code of Federal Regulations, 2010 CFR
2010-04-01
... only: (1) Agent employed to manage the property that has an identity of interest and identity of... individual corporation; company; association; partnership; authority; firm; society; trust; state, local government or agency thereof; or any other organization or group of people. (4) Multifamily property...
Smoluchowski Equation for Networks: Merger Induced Intermittent Giant Node Formation and Degree Gap
NASA Astrophysics Data System (ADS)
Goto, Hayato; Viegas, Eduardo; Jensen, Henrik Jeldtoft; Takayasu, Hideki; Takayasu, Misako
2018-06-01
The dynamical phase diagram of a network undergoing annihilation, creation, and coagulation of nodes is found to exhibit two regimes controlled by the combined effect of preferential attachment for initiator and target nodes during coagulation and for link assignment to new nodes. The first regime exhibits smooth dynamics and power law degree distributions. In the second regime, giant degree nodes and gaps in the degree distribution are formed intermittently. Data for the Japanese firm network in 1994 and 2014 suggests that this network is moving towards the intermittent switching region.
The value of less connected agents in Boolean networks
NASA Astrophysics Data System (ADS)
Epstein, Daniel; Bazzan, Ana L. C.
2013-11-01
In multiagent systems, agents often face binary decisions where one seeks to take either the minority or the majority side. Examples are minority and congestion games in general, i.e., situations that require coordination among the agents in order to depict efficient decisions. In minority games such as the El Farol Bar Problem, previous works have shown that agents may reach appropriate levels of coordination, mostly by looking at the history of past decisions. Not many works consider any kind of structure of the social network, i.e., how agents are connected. Moreover, when structure is indeed considered, it assumes some kind of random network with a given, fixed connectivity degree. The present paper departs from the conventional approach in some ways. First, it considers more realistic network topologies, based on preferential attachments. This is especially useful in social networks. Second, the formalism of random Boolean networks is used to help agents to make decisions given their attachments (for example acquaintances). This is coupled with a reinforcement learning mechanism that allows agents to select strategies that are locally and globally efficient. Third, we use agent-based modeling and simulation, a microscopic approach, which allows us to draw conclusions about individuals and/or classes of individuals. Finally, for the sake of illustration we use two different scenarios, namely the El Farol Bar Problem and a binary route choice scenario. With this approach we target systems that adapt dynamically to changes in the environment, including other adaptive decision-makers. Our results using preferential attachments and random Boolean networks are threefold. First we show that an efficient equilibrium can be achieved, provided agents do experimentation. Second, microscopic analysis show that influential agents tend to consider few inputs in their Boolean functions. Third, we have also conducted measurements related to network clustering and centrality that help to see how agents are organized.
Cooperation in N-person evolutionary snowdrift game in scale-free Barabási Albert networks
NASA Astrophysics Data System (ADS)
Lee, K. H.; Chan, Chun-Him; Hui, P. M.; Zheng, Da-Fang
2008-09-01
Cooperation in the N-person evolutionary snowdrift game (NESG) is studied in scale-free Barabási-Albert (BA) networks. Due to the inhomogeneity of the network, two versions of NESG are proposed and studied. In a model where the size of the competing group varies from agent to agent, the fraction of cooperators drops as a function of the payoff parameter. The networking effect is studied via the fraction of cooperative agents for nodes with a particular degree. For small payoff parameters, it is found that the small- k agents are dominantly cooperators, while large- k agents are of non-cooperators. Studying the spatial correlation reveals that cooperative agents will avoid to be nearest neighbors and the correlation disappears beyond the next-nearest neighbors. The behavior can be explained in terms of the networking effect and payoffs. In another model with a fixed size of competing groups, the fraction of cooperators could show a non-monotonic behavior in the regime of small payoff parameters. This non-trivial behavior is found to be a combined effect of the many agents with the smallest degree in the BA network and the increasing fraction of cooperators among these agents with the payoff for small payoffs.
Efficient priority queueing routing strategy on networks of mobile agents
NASA Astrophysics Data System (ADS)
Wu, Gan-Hua; Yang, Hui-Jie; Pan, Jia-Hui
2018-03-01
As a consequence of their practical implications for communications networks, traffic dynamics on complex networks have recently captivated researchers. Previous routing strategies for improving transport efficiency have paid little attention to the orders in which the packets should be forwarded, just simply used first-in-first-out queue discipline. Here, we apply a priority queuing discipline and propose a shortest-distance-first routing strategy on networks of mobile agents. Numerical experiments reveal that the proposed scheme remarkably improves both the network throughput and the packet arrival rate and reduces both the average traveling time and the rate of waiting time to traveling time. Moreover, we find that the network capacity increases with an increase in both the communication radius and the number of agents. Our work may be helpful for the design of routing strategies on networks of mobile agents.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-11-21
... updating and revising a set of production, underwriting, asset management, closing, and other documents... clarify the requirements for a management agent and the management agreement. Production--Firm Commitments... closing documents to the Office of Management and Budget (OMB) for review and approval, and assignment of...
78 FR 8177 - Proposed Flood Hazard Determinations
Federal Register 2010, 2011, 2012, 2013, 2014
2013-02-05
... insurance agents and others to calculate appropriate flood insurance premium rates for new buildings and the contents of those buildings. DATES: Comments are to be submitted on or before May 6, 2013. ADDRESSES: The... buildings built after the FIRM and FIS report become effective. The communities affected by the flood hazard...
A Method for Decentralised Optimisation in Networks
NASA Astrophysics Data System (ADS)
Saramäki, Jari
2005-06-01
We outline a method for distributed Monte Carlo optimisation of computational problems in networks of agents, such as peer-to-peer networks of computers. The optimisation and messaging procedures are inspired by gossip protocols and epidemic data dissemination, and are decentralised, i.e. no central overseer is required. In the outlined method, each agent follows simple local rules and seeks for better solutions to the optimisation problem by Monte Carlo trials, as well as by querying other agents in its local neighbourhood. With proper network topology, good solutions spread rapidly through the network for further improvement. Furthermore, the system retains its functionality even in realistic settings where agents are randomly switched on and off.
Pattern Analysis in Social Networks with Dynamic Connections
NASA Astrophysics Data System (ADS)
Wu, Yu; Zhang, Yu
In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Most existing work in this area models social network in which agent relations are fixed; instead, we focus on dynamic social networks where agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation rule called the Highest Weighted Reward (HWR) rule, with which agents dynamically choose their neighbors in order to maximize their own utilities based on the rewards from previous interactions. Our experiments show that in the 2-action pure coordination game, our system will stabilize to a clustering state where all relationships in the network are rewarded with the optimal payoff. Our experiments also reveal additional interesting patterns in the network.
NASA Astrophysics Data System (ADS)
Torre, Gerardo De La; Yucelen, Tansel
2018-03-01
Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise components can easily result in system instability and prohibit the accomplishment of system-level objectives. In this paper, we study resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e. agents that are subject to exogenous disturbances that represent a class of adverse conditions. In particular, a distributed adaptive control architecture is presented for directed and time-varying graph topologies to retrieve a desired networked multiagent system behaviour. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we show that the considered class of adverse conditions can be mitigated by the proposed adaptive control approach that utilises a local state emulator - even if all agents are misbehaving. Illustrative numerical examples are provided to demonstrate the theoretical findings.
Ecology Based Decentralized Agent Management System
NASA Technical Reports Server (NTRS)
Peysakhov, Maxim D.; Cicirello, Vincent A.; Regli, William C.
2004-01-01
The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.
Self-organizing network services with evolutionary adaptation.
Nakano, Tadashi; Suda, Tatsuya
2005-09-01
This paper proposes a novel framework for developing adaptive and scalable network services. In the proposed framework, a network service is implemented as a group of autonomous agents that interact in the network environment. Agents in the proposed framework are autonomous and capable of simple behaviors (e.g., replication, migration, and death). In this paper, an evolutionary adaptation mechanism is designed using genetic algorithms (GAs) for agents to evolve their behaviors and improve their fitness values (e.g., response time to a service request) to the environment. The proposed framework is evaluated through simulations, and the simulation results demonstrate the ability of autonomous agents to adapt to the network environment. The proposed framework may be suitable for disseminating network services in dynamic and large-scale networks where a large number of data and services need to be replicated, moved, and deleted in a decentralized manner.
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…
Residual Network Data Structures in Android Devices
2011-09-01
Apple’s iOS, Google’s Android, RIM’s Blackberry and Nokia’s Symbian. Each Smartphone presents unique characteristics for forensic examiners. In...another. • Home Agent: A router on mobile node’s home network that tunnels traffic to mobile node when not on home network. Also maintains mobile nodes...Address notification to the Home Agent. When traffic arrives at the Home Agent for the mobile node, the Home Agent tunnels the traffic to the Care-of
Understanding interfirm relationships in business ecosystems with interactive visualization.
Basole, Rahul C; Clear, Trustin; Hu, Mengdie; Mehrotra, Harshit; Stasko, John
2013-12-01
Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks. Existing tools, however, are predominantly query- or list-centric with limited interactive, exploratory capabilities. Guided by a field study of corporate analysts, we have designed and implemented dotlink360, an interactive visualization system that provides capabilities to gain systemic insight into the compositional, temporal, and connective characteristics of business ecosystems. dotlink360 consists of novel, multiple connected views enabling the analyst to explore, discover, and understand interfirm networks for a focal firm, specific market segments or countries, and the entire business ecosystem. System evaluation by a small group of prototypical users shows supporting evidence of the benefits of our approach. This design study contributes to the relatively unexplored, but promising area of exploratory information visualization in market research and business strategy.
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.
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.
When the firm prevents the crash: Avoiding market collapse with partial control.
Levi, Asaf; Sabuco, Juan; A F Sanjuán, Miguel
2017-01-01
Market collapse is one of the most dramatic events in economics. Such a catastrophic event can emerge from the nonlinear interactions between the economic agents at the micro level of the economy. Transient chaos might be a good description of how a collapsing market behaves. In this work, we apply a new control method, the partial control method, with the goal of avoiding this disastrous event. Contrary to common control methods that try to influence the system from the outside, here the market is controlled from the bottom up by one of the most basic components of the market-the firm. This is the first time that the partial control method is applied on a strictly economical system in which we also introduce external disturbances. We show how the firm is capable of controlling the system avoiding the collapse by only adjusting the selling price of the product or the quantity of production in accordance to the market circumstances. Additionally, we demonstrate how a firm with a large market share is capable of influencing the demand achieving price stability across the retail and wholesale markets. Furthermore, we prove that the control applied in both cases is much smaller than the external disturbances.
A practical guide to social networks.
Cross, Rob; Liedtka, Jeanne; Weiss, Leigh
2005-03-01
Saying that networks are important is stating the obvious. But harnessing the power of these seemingly invisible groups to achieve organizational goals is an elusive undertaking. Most efforts to promote collaboration are haphazard and built on the implicit philosophy that more connectivity is better. In truth, networks create relational demands that sap people's time and energy and can bog down entire organizations. It's crucial for executives to learn how to promote connectivity only where it benefits an organization or individual and to decrease unnecessary connections. In this article, the authors introduce three types of social networks, each of which delivers unique value. The customized response network excels at framing the ambiguous problems involved in innovation. Strategy consulting firms and new-product development groups rely on this format. By contrast, surgical teams and law firms rely mostly on the modular response network, which works best when components of the problem are known but the sequence of those components in the solution is unknown. And the routine response network is best suited for organizations like call centers, where the problems and solutions are fairly predictable but collaboration is still needed. Executives shouldn't simply hope that collaboration will spontaneously occur in the right places atthe right times in their organization. They need to develop a strategic, nuanced view of collaboration, and they must take steps to ensure that their companies support the types of social networks that best fit their goals. Drawing on examples from Novartis, the FAA, and Sallie Mae, the authors offer managers the tools they need to determine which network will deliver the best results for their organizations and which strategic investments will nurture the right degree of connectivity.
The social architecture of capitalism
NASA Astrophysics Data System (ADS)
Wright, Ian
2005-02-01
A dynamic model of the social relations between workers and capitalists is introduced. The model self-organises into a dynamic equilibrium with statistical properties that are in close qualitative and in many cases quantitative agreement with a broad range of known empirical distributions of developed capitalism, including the power-law firm size distribution, the Laplace firm and GDP growth distribution, the lognormal firm demises distribution, the exponential recession duration distribution, the lognormal-Pareto income distribution, and the gamma-like firm rate-of-profit distribution. Normally these distributions are studied in isolation, but this model unifies and connects them within a single causal framework. The model also generates business cycle phenomena, including fluctuating wage and profit shares in national income about values consistent with empirical studies. The generation of an approximately lognormal-Pareto income distribution and an exponential-Pareto wealth distribution demonstrates that the power-law regime of the income distribution can be explained by an additive process on a power-law network that models the social relation between employers and employees organised in firms, rather than a multiplicative process that models returns to investment in financial markets. A testable consequence of the model is the conjecture that the rate-of-profit distribution is consistent with a parameter-mix of a ratio of normal variates with means and variances that depend on a firm size parameter that is distributed according to a power-law.
Using hybrid method to evaluate the green performance in uncertainty.
Tseng, Ming-Lang; Lan, Lawrence W; Wang, Ray; Chiu, Anthony; Cheng, Hui-Ping
2011-04-01
Green performance measure is vital for enterprises in making continuous improvements to maintain sustainable competitive advantages. Evaluation of green performance, however, is a challenging task due to the dependence complexity of the aspects, criteria, and the linguistic vagueness of some qualitative information and quantitative data together. To deal with this issue, this study proposes a novel approach to evaluate the dependence aspects and criteria of firm's green performance. The rationale of the proposed approach, namely green network balanced scorecard, is using balanced scorecard to combine fuzzy set theory with analytical network process (ANP) and importance-performance analysis (IPA) methods, wherein fuzzy set theory accounts for the linguistic vagueness of qualitative criteria and ANP converts the relations among the dependence aspects and criteria into an intelligible structural modeling used IPA. For the empirical case study, four dependence aspects and 34 green performance criteria for PCB firms in Taiwan were evaluated. The managerial implications are discussed.
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.
Characteristics of group networks in the KOSPI and the KOSDAQ
NASA Astrophysics Data System (ADS)
Kim, Kyungsik; Ko, Jeung-Su; Yi, Myunggi
2012-02-01
We investigate the main feature of group networks in the KOSPI and KOSDAQ of Korean financial markets and analyze daily cross-correlations between price fluctuations for the 5-year time period from 2006 to 2010. We discuss the stabilities by undressing the market-wide effect using the Markowitz multi-factor model and the network-based approach. In particular we ascertain the explicit list of significant firms in the few largest eigenvectors from the undressed correlation matrix. Finally, we show the structure of group correlation by applying a network-based approach. In addition, the relation between market capitalizations and businesses is examined.
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 general equilibrium model of a production economy with asset markets
NASA Astrophysics Data System (ADS)
Raberto, Marco; Teglio, Andrea; Cincotti, Silvano
2006-10-01
In this paper, a general equilibrium model of a monetary production economy is presented. The model is characterized by three classes of agents: a representative firm, heterogeneous households, and the government. Two markets (i.e., a labour market and a goods market, are considered) and two assets are traded in exchange of money, namely, government bonds and equities. Households provide the labour force and decide on consumption and savings, whereas the firm provides consumption goods and demands labour. The government receives taxes from households and pays interests on debt. The Walrasian equilibrium is derived analytically. The dynamics through quantity constrained equilibria out from the Walrasian equilibrium is also studied by means of computer simulations.
Organization of complex networks
NASA Astrophysics Data System (ADS)
Kitsak, Maksim
Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how epidemics spread though networks. Our results indicate that a virus is more likely to infect a large area of a network if it originates at a node contained within k-core of high index k.
A multi-agent intelligent environment for medical knowledge.
Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder
2003-03-01
AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).
USDA-ARS?s Scientific Manuscript database
The large fire ant decapitating fly, Pseudacteon litoralis Borgmeier from northeastern Argentina was successfully released as a self-sustaining biocontrol agent of imported fire ants in south central Alabama in 2005. Five years later, this fly is firmly established at this site and has expanded out...
Agent of Whirling Disease Meets Orphan Worm: Phylogenomic Analyses Firmly Place Myxozoa in Cnidaria
Nesnidal, Maximilian P.; Helmkampf, Martin; Bruchhaus, Iris; El-Matbouli, Mansour; Hausdorf, Bernhard
2013-01-01
Myxozoa are microscopic obligate endoparasites with complex live cycles. Representatives are Myxobolus cerebralis, the causative agent of whirling disease in salmonids, and the enigmatic “orphan worm” Buddenbrockia plumatellae parasitizing in Bryozoa. Originally, Myxozoa were classified as protists, but later several metazoan characteristics were reported. However, their phylogenetic relationships remained doubtful. Some molecular phylogenetic analyses placed them as sister group to or even within Bilateria, whereas the possession of polar capsules that are similar to nematocysts of Cnidaria and of minicollagen genes suggest a close relationship between Myxozoa and Cnidaria. EST data of Buddenbrockia also indicated a cnidarian origin of Myxozoa, but were not sufficient to reject a closer relationship to bilaterians. Phylogenomic analyses of new genomic sequences of Myxobolus cerebralis firmly place Myxozoa as sister group to Medusozoa within Cnidaria. Based on the new dataset, the alternative hypothesis that Myxozoa form a clade with Bilateria can be rejected using topology tests. Sensitivity analyses indicate that this result is not affected by long branch attraction artifacts or compositional bias. PMID:23382916
Enhancing technological innovation in small firms: Role of collaboration
NASA Astrophysics Data System (ADS)
Singh, D.; Khamba, J. S.; Nanda, T.
2014-07-01
Contribution of Micro-Small and Medium Enterprises (MSMEs) is highly remarkable in the overall industrial economy of the country. In recent years, the MSME sector has consistently registered higher growth rate compared to the overall industrial sector. With its agility and dynamism, the sector has shown admirable innovativeness and adaptability to survive the recent economic downturn and recession. However, MSMEs growth rate is still at low level. Therefore, it becomes essential for organizations to adopt new technologies or upgrade existing setup to meet continuously changing global market and fulfill customer needs. This paper explores the relationships between different collaboration networks and technological innovation of small firms through an extensive review of literature. The study finds that collaboration with larger enterprises, R&D institutions, universities and government agencies play a significant role in enhancing technological innovation in small firms.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.
Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan
2018-02-02
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.
Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management
2018-01-01
One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884
RTML: remote telescope markup language and you
NASA Astrophysics Data System (ADS)
Hessman, F. V.
2001-12-01
In order to coordinate the use of robotic and remotely operated telescopes in networks -- like Göttingen's MOnitoring NEtwork of Telescopes (MONET) -- a standard format for the exchange of observing requests and reports is needed. I describe the benefits of Remote Telescope Markup Language (RTML), an XML-based protocol originally developed by the Hands-On Universe Project, which is being used and further developed by several robotic telescope projects and firms.
Building Collaborative Capacity for Homeland Security
2004-11-01
Kesner, I. F. (1993). Top Managerial Prestige, Power and Tender Offer Response - a Study of Elite Social Networks and Target Firm Cooperation During...Organization Science, 12(3), 372-388. Galaskiewicz, J., & Burt, R. S. (1991). Interorganization Contagion in Corporate Philanthropy . Administrative
Suppressing epidemic spreading by risk-averse migration in dynamical networks
NASA Astrophysics Data System (ADS)
Yang, Han-Xin; Tang, Ming; Wang, Zhen
2018-01-01
In this paper, we study the interplay between individual behaviors and epidemic spreading in a dynamical network. We distribute agents on a square-shaped region with periodic boundary conditions. Every agent is regarded as a node of the network and a wireless link is established between two agents if their geographical distance is less than a certain radius. At each time, every agent assesses the epidemic situation and make decisions on whether it should stay in or leave its current place. An agent will leave its current place with a speed if the number of infected neighbors reaches or exceeds a critical value E. Owing to the movement of agents, the network's structure is dynamical. Interestingly, we find that there exists an optimal value of E leading to the maximum epidemic threshold. This means that epidemic spreading can be effectively controlled by risk-averse migration. Besides, we find that the epidemic threshold increases as the recovering rate increases, decreases as the contact radius increases, and is maximized by an optimal moving speed. Our findings offer a deeper understanding of epidemic spreading in dynamical networks.
Bosse, Stefan
2015-01-01
Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques. PMID:25690550
Bosse, Stefan
2015-02-16
Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.
Optimal forwarding ratio on dynamical networks with heterogeneous mobility
NASA Astrophysics Data System (ADS)
Gan, Yu; Tang, Ming; Yang, Hanxin
2013-05-01
Since the discovery of non-Poisson statistics of human mobility trajectories, more attention has been paid to understand the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate packet forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged at small and large high-speed value. It is also interesting to find that a slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from the local structural heterogeneity of low-speed agents.
Research of negotiation in network trade system based on multi-agent
NASA Astrophysics Data System (ADS)
Cai, Jun; Wang, Guozheng; Wu, Haiyan
2009-07-01
A construction and implementation technology of network trade based on multi-agent is described in this paper. First, we researched the technology of multi-agent, then we discussed the consumer's behaviors and the negotiation between purchaser and bargainer which emerges in the traditional business mode and analysed the key technology to implement the network trade system. Finally, we implement the system.
Agent Collaborative Target Localization and Classification in Wireless Sensor Networks
Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng
2007-01-01
Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.
NASA Astrophysics Data System (ADS)
Yang, Hong-Yong; Lu, Lan; Cao, Ke-Cai; Zhang, Si-Ying
2010-04-01
In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.
Agent-based real-time signal coordination in congested networks.
DOT National Transportation Integrated Search
2014-01-01
This study is the continuation of a previous NEXTRANS study on agent-based reinforcement : learning methods for signal coordination in congested networks. In the previous study, the : formulation of a real-time agent-based traffic signal control in o...
An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network
Brennan, Robert W.
2017-01-01
With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452
NASA Astrophysics Data System (ADS)
Anghel, M.; Toroczkai, Zoltán; Bassler, Kevin E.; Korniss, G.
2004-02-01
Using the minority game as a model for competition dynamics, we investigate the effects of interagent communications across a network on the global evolution of the game. Agent communication across this network leads to the formation of an influence network, which is dynamically coupled to the evolution of the game, and it is responsible for the information flow driving the agents' actions. We show that the influence network spontaneously develops hubs with a broad distribution of in-degrees, defining a scale-free robust leadership structure. Furthermore, in realistic parameter ranges, facilitated by information exchange on the network, agents can generate a high degree of cooperation making the collective almost maximally efficient.
An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.
Taboun, Mohammed S; Brennan, Robert W
2017-09-14
With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.
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
NASA Astrophysics Data System (ADS)
Wattawa, Scott
1995-11-01
Offering interactive services and data in a hybrid fiber/coax cable system requires the coordination of a host of operations and business support systems. New service offerings and network growth and evolution create never-ending changes in the network infrastructure. Agent-based enterprise models provide a flexible mechanism for systems integration of service and support systems. Agent models also provide a mechanism to decouple interactive services from network architecture. By using the Java programming language, agents may be made safe, portable, and intelligent. This paper investigates the application of the Object Management Group's Common Object Request Brokering Architecture to the integration of a multiple services metropolitan area network.
Formation of Common Investment Networks by Project Establishment between Agents
NASA Astrophysics Data System (ADS)
Navarro-Barrientos, Jesús Emeterio
We present an investment model integrated with trust and reputation mechanisms where agents interact with each other to establish investment projects. We investigate the establishment of investment projects, the influence of the interaction between agents in the evolution of the distribution of wealth as well as the formation of common investment networks and some of their properties. Simulation results show that the wealth distribution presents a power law in its tail. Also, it is shown that the trust and reputation mechanism proposed leads to the establishment of networks among agents, presenting some of the typical characteristics of real-life networks like a high clustering coefficient and short average path length.
Constant Price of Anarchy in Network Creation Games via Public Service Advertising
NASA Astrophysics Data System (ADS)
Demaine, Erik D.; Zadimoghaddam, Morteza
Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others, without paying much to construct the network. Many generalizations have been considered, including non-uniform interests between nodes, general graphs of allowable edges, bounded budget agents, etc. In all of these settings, there is no known constant bound on the price of anarchy. In fact, in many cases, the price of anarchy can be very large, namely, a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand, the price of stability in all these models is constant, which means that there is chance that agents act selfishly and we end up with a reasonable social cost.
Design, Implementation and Case Study of WISEMAN: WIreless Sensors Employing Mobile AgeNts
NASA Astrophysics Data System (ADS)
González-Valenzuela, Sergio; Chen, Min; Leung, Victor C. M.
We describe the practical implementation of Wiseman: our proposed scheme for running mobile agents in Wireless Sensor Networks. Wiseman’s architecture derives from a much earlier agent system originally conceived for distributed process coordination in wired networks. Given the memory constraints associated with small sensor devices, we revised the architecture of the original agent system to make it applicable to this type of networks. Agents are programmed as compact text scripts that are interpreted at the sensor nodes. Wiseman is currently implemented in TinyOS ver. 1, its binary image occupies 19Kbytes of ROM memory, and it occupies 3Kbytes of RAM to operate. We describe the rationale behind Wiseman’s interpreter architecture and unique programming features that can help reduce packet overhead in sensor networks. In addition, we gauge the proposed system’s efficiency in terms of task duration with different network topologies through a case study that involves an early-fire-detection application in a fictitious forest setting.
Strategic Downsizing and Learning Organisations.
ERIC Educational Resources Information Center
Griggs, Harvey E.; Hyland, Paul
2003-01-01
Downsizing or brain drain may damage the learning capacity of organizations. A case study of an aerospace manufacturing firm shows that appropriate strategies to analyze the impact on formal and informal learning networks may help manage or minimize the damage. (Contains 55 references.) (SK)
Agents, Bayes, and Climatic Risks - a modular modelling approach
NASA Astrophysics Data System (ADS)
Haas, A.; Jaeger, C.
2005-08-01
When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine.
Maramaldi, Giada; Togni, Stefano; Franceschi, Federico; Lati, Elian
2014-01-01
Purpose The aim of this study was to investigate the topical efficacy of a new purified extract from Madagascar, Gotu Kola (Centella asiatica [L.] Urban), both on human explants and on human volunteers, in relation to skin wrinkling and skin protection against ultraviolet light exposure. The extract, with a peculiar content of biologically active molecules, was investigated as a novel anti-inflammaging and antiglycation agent. Its typical terpenes, known as collagen synthesis promoters, represent at least 45% of the extract. It also contains a polyphenolic fraction cooperating to the observed properties. Methods C. asiatica purified extract was assayed on human skin explants maintained alive, and several parameters were evaluated. Among the most relevant, the thymine dimerization was evaluated by immunostaining. Malondialdehyde formation was evaluated as free-radical scavenging marker by enzyme-linked immunosorbent assay. The expression of interleukin-1α was observed by enzyme-linked immunosorbent assay as well. The product was further evaluated as an antiglycation agent, being glycation quantified by the advanced glycation product carboxymethyl lysine. C. asiatica purified extract was also evaluated as an antiwrinkling agent in a single-blind, placebo-controlled study. Formulated in a simple oil-in-water emulsion, the extent of wrinkling was assessed by skin replicas, skin firmness, skin elasticity, and collagen density measurements. Results C. asiatica purified extract could protect DNA from ultraviolet light-induced damage, decreasing the thymine photodimerization by over 28% (P<0.05). A reduced (26%, P<0.01) expression of interleukin-1α was also observed, supporting its anti-inflammatory potential. C. asiatica purified extract showed in vitro a total inhibition of carboxymethyl lysine formation induced by the glycating agent methylglyoxal. A clear epidermal densification of collagen network in the papillary dermis was observed. These in vitro data have been confirmed by clinical results. Conclusion These results qualify C. asiatica purified extract as an antiaging ingredient, addressing skin damage caused by inflammaging and glycation by relying on the synergy of triterpens and polyphenolics. PMID:24376360
Maramaldi, Giada; Togni, Stefano; Franceschi, Federico; Lati, Elian
2014-01-01
The aim of this study was to investigate the topical efficacy of a new purified extract from Madagascar, Gotu Kola (Centella asiatica [L.] Urban), both on human explants and on human volunteers, in relation to skin wrinkling and skin protection against ultraviolet light exposure. The extract, with a peculiar content of biologically active molecules, was investigated as a novel anti-inflammaging and antiglycation agent. Its typical terpenes, known as collagen synthesis promoters, represent at least 45% of the extract. It also contains a polyphenolic fraction cooperating to the observed properties. C. asiatica purified extract was assayed on human skin explants maintained alive, and several parameters were evaluated. Among the most relevant, the thymine dimerization was evaluated by immunostaining. Malondialdehyde formation was evaluated as free-radical scavenging marker by enzyme-linked immunosorbent assay. The expression of interleukin-1α was observed by enzyme-linked immunosorbent assay as well. The product was further evaluated as an antiglycation agent, being glycation quantified by the advanced glycation product carboxymethyl lysine. C. asiatica purified extract was also evaluated as an antiwrinkling agent in a single-blind, placebo-controlled study. Formulated in a simple oil-in-water emulsion, the extent of wrinkling was assessed by skin replicas, skin firmness, skin elasticity, and collagen density measurements. C. asiatica purified extract could protect DNA from ultraviolet light-induced damage, decreasing the thymine photodimerization by over 28% (P<0.05). A reduced (26%, P<0.01) expression of interleukin-1α was also observed, supporting its anti-inflammatory potential. C. asiatica purified extract showed in vitro a total inhibition of carboxymethyl lysine formation induced by the glycating agent methylglyoxal. A clear epidermal densification of collagen network in the papillary dermis was observed. These in vitro data have been confirmed by clinical results. These results qualify C. asiatica purified extract as an antiaging ingredient, addressing skin damage caused by inflammaging and glycation by relying on the synergy of triterpens and polyphenolics.
Small employers and self-insured health benefits: too small to succeed?
Yee, Tracy; Christianson, Jon B; Ginsburg, Paul B
2012-07-01
Over the past decade, large employers increasingly have bypassed traditional health insurance for their workers, opting instead to assume the financial risk of enrollees' medical care through self-insurance. Because self-insurance arrangements may offer advantages--such as lower costs, exemption from most state insurance regulation and greater flexibility in benefit design--they are especially attractive to large firms with enough employees to spread risk adequately to avoid the financial fallout from potentially catastrophic medical costs of some employees. Recently, with rising health care costs and changing market dynamics, more small firms--100 or fewer workers--are interested in self-insuring health benefits, according to a new qualitative study from the Center for Studying Health System Change (HSC). Self-insured firms typically use a third-party administrator (TPA) to process medical claims and provide access to provider networks. Firms also often purchase stop-loss insurance to cover medical costs exceeding a predefined amount. Increasingly competitive markets for TPA services and stop-loss insurance are making self-insurance attractive to more employers. The 2010 national health reform law imposes new requirements and taxes on health insurance that may spur more small firms to consider self-insurance. In turn, if more small firms opt to self-insure, certain health reform goals, such as strengthening consumer protections and making the small-group health insurance market more viable, may be undermined. Specifically, adverse selection--attracting sicker-than-average people--is a potential issue for the insurance exchanges created by reform.
Generation capacity expansion planning in deregulated electricity markets
NASA Astrophysics Data System (ADS)
Sharma, Deepak
With increasing demand of electric power in the context of deregulated electricity markets, a good strategic planning for the growth of the power system is critical for our tomorrow. There is a need to build new resources in the form of generation plants and transmission lines while considering the effects of these new resources on power system operations, market economics and the long-term dynamics of the economy. In deregulation, the exercise of generation planning has undergone a paradigm shift. The first stage of generation planning is now undertaken by the individual investors. These investors see investments in generation capacity as an increasing business opportunity because of the increasing market prices. Therefore, the main objective of such a planning exercise, carried out by individual investors, is typically that of long-term profit maximization. This thesis presents some modeling frameworks for generation capacity expansion planning applicable to independent investor firms in the context of power industry deregulation. These modeling frameworks include various technical and financing issues within the process of power system planning. The proposed modeling frameworks consider the long-term decision making process of investor firms, the discrete nature of generation capacity addition and incorporates transmission network modeling. Studies have been carried out to examine the impact of the optimal investment plans on transmission network loadings in the long-run by integrating the generation capacity expansion planning framework within a modified IEEE 30-bus transmission system network. The work assesses the importance of arriving at an optimal IRR at which the firm's profit maximization objective attains an extremum value. The mathematical model is further improved to incorporate binary variables while considering discrete unit sizes, and subsequently to include the detailed transmission network representation. The proposed models are novel in the sense that the planning horizon is split into plan sub-periods so as to minimize the overall risks associated with long-term plan models, particularly in the context of deregulation.
Kawamoto, Hirokazu; Takayasu, Hideki; Jensen, Henrik Jeldtoft; Takayasu, Misako
2015-01-01
Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition.
Domain-wall trapping in a ferromagnetic nanowire network
NASA Astrophysics Data System (ADS)
Saitoh, E.; Tanaka, M.; Miyajima, H.; Yamaoka, T.
2003-05-01
The magnetic domain configuration in a submicron Ni81Fe19 wire network has been investigated by magnetic force microscopy. To improve the responsivity of the magnetic force microscope, an active quality factor autocontrol method was adopted. In the remanent state, domain walls were observed trapped firmly at the vertexes of the network. The magnetic domain configurations appear to minimize the exchange energy at the vertexes. These results indicate that the magnetic property of the ferromagnetic network can be described in terms of the uniform magnetic moments of the wires and interwire magnetic interactions at the vertexes. The observed structure of the domain walls is well reproduced by micromagnetic simulations.
Casting a Statewide Strategic Performance Net: Interlaced Data and Responsive Supports
ERIC Educational Resources Information Center
Layland, Allison; Redding, Sam
2017-01-01
The pivot point for educational change is now firmly placed with the district, rebalancing the position of the state and the school relative to the local education agency (LEA). The state education agency (SEA) has been shifting its emphasis for decades, from a compliance-focused authority to a change agent equipped with systems, processes,…
ERIC Educational Resources Information Center
Abegaz, Melaku
2016-01-01
This dissertation studies the effects of foreign presence on the performance of domestic institutions and economic agents. We identify three types of foreign presence: international students, inward foreign investment, and exporting activities. The first chapter investigates the impacts of international students on the graduation performance of…
Collective helping and bystander effects in coevolving helping networks.
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.
When the firm prevents the crash: Avoiding market collapse with partial control
2017-01-01
Market collapse is one of the most dramatic events in economics. Such a catastrophic event can emerge from the nonlinear interactions between the economic agents at the micro level of the economy. Transient chaos might be a good description of how a collapsing market behaves. In this work, we apply a new control method, the partial control method, with the goal of avoiding this disastrous event. Contrary to common control methods that try to influence the system from the outside, here the market is controlled from the bottom up by one of the most basic components of the market—the firm. This is the first time that the partial control method is applied on a strictly economical system in which we also introduce external disturbances. We show how the firm is capable of controlling the system avoiding the collapse by only adjusting the selling price of the product or the quantity of production in accordance to the market circumstances. Additionally, we demonstrate how a firm with a large market share is capable of influencing the demand achieving price stability across the retail and wholesale markets. Furthermore, we prove that the control applied in both cases is much smaller than the external disturbances. PMID:28832608
Knowledge Diffusion on Networks through the Game Strategy
NASA Astrophysics Data System (ADS)
Sun, Shu; Wu, Jiangning; Xuan, Zhaoguo
In this paper, we develop a knowledge diffusion model in which agents determine to give their knowledge to others according to some exchange strategies. The typical network namely small-world network is used for modeling, on which agents with knowledge are viewed as the nodes of the network and the edges are viewed as the social relationships for knowledge transmission. Such agents are permitted to interact with their neighbors repeatedly who have direct connections with them and accordingly change their strategies by choosing the most beneficial neighbors to diffuse knowledge. Two kinds of knowledge transmission strategies are proposed for the theoretical model based on the game theory and thereafter used in different simulations to examine the effect of the network structure on the knowledge diffusion effect. By analyses, two main observations can be found: One is that the simulation results are contrary to our intuition which agents would like to only accept but not share, thus they will maximize their benefit; another one is that the number of the agents acquired knowledge and the corresponding knowledge stock turn out to be independent of the percentage of those agents who choose to contribute their knowledge.
Social Networks as a Source of Competitive Advantage for the Firm.
ERIC Educational Resources Information Center
Van Laere, Kristien; Heene, Aime
2003-01-01
Proposes a conceptual framework for managing relationships of small and medium-sized enterprises, based on the necessity of cooperation for survival. Describes characteristics of embedded relationship in stakeholder interactions, including trust, durability, information transfer, and collaboration. (Contains 72 references.) (SK)
Judge says leading viatical firm violated securities laws.
1995-09-22
A Federal judge has agreed with the Securities and Exchange Commission (SEC) in its suit against Life Partners, a leading viatical settlement company. According to the SEC, Life Partners buys insurance policies from persons living with AIDS in its own name and then sells interests in these policies to investors. The SEC alleges that these interests fall under the Federal securities laws. Life Partners contends that it acts solely as an agent on behalf of investors, and therefore securities laws do not apply. The judge's injunction requires Life Partners to transfer its insurance policies to an independent agent until the case is resolved.
NASA Astrophysics Data System (ADS)
Izadi, Arman; Kimiagari, Ali mohammad
2014-01-01
Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14% reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.
NASA Astrophysics Data System (ADS)
Izadi, Arman; Kimiagari, Ali Mohammad
2014-05-01
Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.
Uncovering Offshore Financial Centers: Conduits and Sinks in the Global Corporate Ownership Network.
Garcia-Bernardo, Javier; Fichtner, Jan; Takes, Frank W; Heemskerk, Eelke M
2017-07-24
Multinational corporations use highly complex structures of parents and subsidiaries to organize their operations and ownership. Offshore Financial Centers (OFCs) facilitate these structures through low taxation and lenient regulation, but are increasingly under scrutiny, for instance for enabling tax avoidance. Therefore, the identification of OFC jurisdictions has become a politicized and contested issue. We introduce a novel data-driven approach for identifying OFCs based on the global corporate ownership network, in which over 98 million firms (nodes) are connected through 71 million ownership relations. This granular firm-level network data uniquely allows identifying both sink-OFCs and conduit-OFCs. Sink-OFCs attract and retain foreign capital while conduit-OFCs are attractive intermediate destinations in the routing of international investments and enable the transfer of capital without taxation. We identify 24 sink-OFCs. In addition, a small set of five countries - the Netherlands, the United Kingdom, Ireland, Singapore and Switzerland - canalize the majority of corporate offshore investment as conduit-OFCs. Each conduit jurisdiction is specialized in a geographical area and there is significant specialization based on industrial sectors. Against the idea of OFCs as exotic small islands that cannot be regulated, we show that many sink and conduit-OFCs are highly developed countries.
Networks of conforming or nonconforming individuals tend to reach satisfactory decisions.
Ramazi, Pouria; Riehl, James; Cao, Ming
2016-11-15
Binary decisions of agents coupled in networks can often be classified into two types: "coordination," where an agent takes an action if enough neighbors are using that action, as in the spread of social norms, innovations, and viral epidemics, and "anticoordination," where too many neighbors taking a particular action causes an agent to take the opposite action, as in traffic congestion, crowd dispersion, and division of labor. Both of these cases can be modeled using linear-threshold-based dynamics, and a fundamental question is whether the individuals in such networks are likely to reach decisions with which they are satisfied. We show that, in the coordination case, and perhaps more surprisingly, also in the anticoordination case, the agents will indeed always tend to reach satisfactory decisions, that is, the network will almost surely reach an equilibrium state. This holds for every network topology and every distribution of thresholds, for both asynchronous and partially synchronous decision-making updates. These results reveal that irregular network topology, population heterogeneity, and partial synchrony are not sufficient to cause cycles or nonconvergence in linear-threshold dynamics; rather, other factors such as imitation or the coexistence of coordinating and anticoordinating agents must play a role.
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).
Towards a Bio-inspired Security Framework for Mission-Critical Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Ren, Wei; Song, Jun; Ma, Zhao; Huang, Shiyong
Mission-critical wireless sensor networks (WSNs) have been found in numerous promising applications in civil and military fields. However, the functionality of WSNs extensively relies on its security capability for detecting and defending sophisticated adversaries, such as Sybil, worm hole and mobile adversaries. In this paper, we propose a bio-inspired security framework to provide intelligence-enabled security mechanisms. This scheme is composed of a middleware, multiple agents and mobile agents. The agents monitor the network packets, host activities, make decisions and launch corresponding responses. Middleware performs an infrastructure for the communication between various agents and corresponding mobility. Certain cognitive models and intelligent algorithms such as Layered Reference Model of Brain and Self-Organizing Neural Network with Competitive Learning are explored in the context of sensor networks that have resource constraints. The security framework and implementation are also described in details.
Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.
Fu, Zhaohao; Hao, Lingxin
2018-01-15
We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.
Agent-based modeling of China's rural-urban migration and social network structure
NASA Astrophysics Data System (ADS)
Fu, Zhaohao; Hao, Lingxin
2018-01-01
We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.
Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models
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
Systemic risk on different interbank network topologies
NASA Astrophysics Data System (ADS)
Lenzu, Simone; Tedeschi, Gabriele
2012-09-01
In this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity.
Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng
2007-01-01
The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223
Exploring the Role of Value Networks for Software Innovation
NASA Astrophysics Data System (ADS)
Morgan, Lorraine; Conboy, Kieran
This paper describes a research-in-progress that aims to explore the applicability and implications of open innovation practices in two firms - one that employs agile development methods and another that utilizes open source software. The open innovation paradigm has a lot in common with open source and agile development methodologies. A particular strength of agile approaches is that they move away from 'introverted' development, involving only the development personnel, and intimately involves the customer in all areas of software creation, supposedly leading to the development of a more innovative and hence more valuable information system. Open source software (OSS) development also shares two key elements of the open innovation model, namely the collaborative development of the technology and shared rights to the use of the technology. However, one shortfall with agile development in particular is the narrow focus on a single customer representative. In response to this, we argue that current thinking regarding innovation needs to be extended to include multiple stakeholders both across and outside the organization. Additionally, for firms utilizing open source, it has been found that their position in a network of potential complementors determines the amount of superior value they create for their customers. Thus, this paper aims to get a better understanding of the applicability and implications of open innovation practices in firms that employ open source and agile development methodologies. In particular, a conceptual framework is derived for further testing.
Propagation, cascades, and agreement dynamics in complex communication and social networks
NASA Astrophysics Data System (ADS)
Lu, Qiming
Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.
Bonhomme, V; Boveroux, P; Brichant, J F; Laureys, S; Boly, M
2012-01-01
This paper reviews the current knowledge about the mechanisms of anesthesia-induced alteration of consciousness. It is now evident that hypnotic anesthetic agents have specific brain targets whose function is hierarchically altered in a dose-dependent manner. Higher order networks, thought to be involved in mental content generation, as well as sub-cortical networks involved in thalamic activity regulation seems to be affected first by increasing concentrations of hypnotic agents that enhance inhibitory neurotransmission. Lower order sensory networks are preserved, including thalamo-cortical connectivity into those networks, even at concentrations that suppress responsiveness, but cross-modal sensory interactions are inhibited. Thalamo-cortical connectivity into the consciousness networks decreases with increasing concentrations of those agents, and is transformed into an anti-correlated activity between the thalamus and the cortex for the deepest levels of sedation, when the subject is non responsive. Future will tell us whether these brain function alterations are also observed with hypnotic agents that mainly inhibit excitatory neurotransmission. The link between the observations made using fMRI and the identified biochemical targets of hypnotic anesthetic agents still remains to be identified.
Feminine Desire in the Age of Satellite Television.
ERIC Educational Resources Information Center
Curtin, Michael
1999-01-01
Contributes to scholarship on global media conglomerates, cultural expression, and feminism. Delineates the corporate logic of culture industries in the neo-network era. Shows, using the television show "Absolutely Fabulous," how media firms benefit from transnational circulation of multiple and alternative representations of feminine…
Structurally Dynamic Spin Market Networks
NASA Astrophysics Data System (ADS)
Horváth, Denis; Kuscsik, Zoltán
The agent-based model of stock price dynamics on a directed evolving complex network is suggested and studied by direct simulation. The stationary regime is maintained as a result of the balance between the extremal dynamics, adaptivity of strategic variables and reconnection rules. The inherent structure of node agent "brain" is modeled by a recursive neural network with local and global inputs and feedback connections. For specific parametric combination the complex network displays small-world phenomenon combined with scale-free behavior. The identification of a local leader (network hub, agent whose strategies are frequently adapted by its neighbors) is carried out by repeated random walk process through network. The simulations show empirically relevant dynamics of price returns and volatility clustering. The additional emerging aspects of stylized market statistics are Zipfian distributions of fitness.
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.
NASA Astrophysics Data System (ADS)
Donges, Jonathan; Lucht, Wolfgang; Wiedermann, Marc; Heitzig, Jobst; Kurths, Jürgen
2015-04-01
In the anthropocene, the rise of global social and economic networks with ever increasing connectivity and speed of interactions, e.g., the internet or global financial markets, is a key challenge for sustainable development. The spread of opinions, values or technologies on these networks, in conjunction with the coevolution of the network structures themselves, underlies nexuses of current concern such as anthropogenic climate change, biodiversity loss or global land use change. To isolate and quantitatively study the effects and implications of network dynamics for sustainable development, we propose an agent-based model of information flow on adaptive networks between myopic harvesters that exploit private renewable resources. In this conceptual model of a network of socio-ecological systems, information on management practices flows between agents via boundedly rational imitation depending on the state of the resource stocks involved in an interaction. Agents can also adapt the structure of their social network locally by preferentially connecting to culturally similar agents with identical management practices and, at the same time, disconnecting from culturally dissimilar agents. Investigating in detail the statistical mechanics of this model, we find that an increasing rate of information flow through faster imitation dynamics or growing density of network connectivity leads to a marked increase in the likelihood of environmental resource collapse. However, we show that an optimal rate of social network adaptation can mitigate this negative effect without loss of social cohesion through network fragmentation. Our results highlight that seemingly immaterial network dynamics of spreading opinions or values can be of large relevance for the sustainable management of socio-ecological systems and suggest smartly conservative network adaptation as a strategy for mitigating environmental collapse. Hence, facing the great acceleration, these network dynamics should be more routinely incorporated in standard models of economic development or integrated assessment models used for evaluating anthropogenic climate change.
Network formation: neighborhood structures, establishment costs, and distributed learning.
Chasparis, Georgios C; Shamma, Jeff S
2013-12-01
We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games.
Guclu, Hasan; Ferrell Bjerke, Elizabeth; Galvan, Jared; Sweeney, Patricia; Potter, Margaret A
2014-01-01
This study explored if and to what extent the laws of U.S. states mirrored the U.S. federal laws for responding to nuclear-radiological emergencies (NREs). Emergency laws from a 12-state sample and the federal government were retrieved and translated into numeric codes representing acting agents, their partner agents, and the purposes of activity in terms of preparedness, response, and recovery. We used network analysis to explore the relationships among agents in terms of legally directed NRE activities. States' legal networks for NREs appear as not highly inclusive, involving an average of 28% of agents among those specified in the federal laws. Certain agents are highly central in NRE networks, so that their capacity and effectiveness might strongly influence an NRE response. State-level lawmakers and planners might consider whether or not greater inclusion of agents, modeled on the federal government laws, would enhance their NRE laws and if more agents should be engaged in planning and policy-making for NRE incidents. Further research should explore if and to what extent legislated NRE directives impose constraints on practical response activities including emergency planning.
Multi-Agent Market Modeling of Foreign Exchange Rates
NASA Astrophysics Data System (ADS)
Zimmermann, Georg; Neuneier, Ralph; Grothmann, Ralph
A market mechanism is basically driven by a superposition of decisions of many agents optimizing their profit. The oeconomic price dynamic is a consequence of the cumulated excess demand/supply created on this micro level. The behavior analysis of a small number of agents is well understood through the game theory. In case of a large number of agents one may use the limiting case that an individual agent does not have an influence on the market, which allows the aggregation of agents by statistic methods. In contrast to this restriction, we can omit the assumption of an atomic market structure, if we model the market through a multi-agent approach. The contribution of the mathematical theory of neural networks to the market price formation is mostly seen on the econometric side: neural networks allow the fitting of high dimensional nonlinear dynamic models. Furthermore, in our opinion, there is a close relationship between economics and the modeling ability of neural networks because a neuron can be interpreted as a simple model of decision making. With this in mind, a neural network models the interaction of many decisions and, hence, can be interpreted as the price formation mechanism of a market.
NASA Astrophysics Data System (ADS)
Yang, Hong-Yong; Zhang, Shun; Zong, Guang-Deng
2011-01-01
In this paper, the trajectory control of multi-agent dynamical systems with exogenous disturbances is studied. Suppose multiple agents composing of a scale-free network topology, the performance of rejecting disturbances for the low degree node and high degree node is analyzed. Firstly, the consensus of multi-agent systems without disturbances is studied by designing a pinning control strategy on a part of agents, where this pinning control can bring multiple agents' states to an expected consensus track. Then, the influence of the disturbances is considered by developing disturbance observers, and disturbance observers based control (DOBC) are developed for disturbances generated by an exogenous system to estimate the disturbances. Asymptotical consensus of the multi-agent systems with disturbances under the composite controller can be achieved for scale-free network topology. Finally, by analyzing examples of multi-agent systems with scale-free network topology and exogenous disturbances, the verities of the results are proved. Under the DOBC with the designed parameters, the trajectory convergence of multi-agent systems is researched by pinning two class of the nodes. We have found that it has more stronger robustness to exogenous disturbances for the high degree node pinned than that of the low degree node pinned.
Dynamic social networks facilitate cooperation in the N-player Prisoner’s Dilemma
NASA Astrophysics Data System (ADS)
Rezaei, Golriz; Kirley, Michael
2012-12-01
Understanding how cooperative behaviour evolves in network communities, where the individual members interact via social dilemma games, is an on-going challenge. In this paper, we introduce a social network based model to investigate the evolution of cooperation in the N-player Prisoner’s Dilemma game. As such, this work complements previous studies focused on multi-player social dilemma games and endogenous networks. Agents in our model, employ different game-playing strategies reflecting varying cognitive capacities. When an agent plays cooperatively, a social link is formed with each of the other N-1 group members. Subsequent cooperative actions reinforce this link. However, when an agent defects, the links in the social network are broken. Computational simulations across a range of parameter settings are used to examine different scenarios: varying population and group sizes; the group formation process (or partner selection); and agent decision-making strategies under varying dilemma constraints (cost-to-benefit ratios), including a “discriminator” strategy where the action is based on a function of the weighted links within an agent’s social network. The simulation results show that the proposed social network model is able to evolve and maintain cooperation. As expected, as the value of N increases the equilibrium proportion of cooperators in the population decreases. In addition, this outcome is dependent on the dilemma constraint (cost-to-benefit ratio). However, in some circumstances the dynamic social network plays an increasingly important role in promoting and sustaining cooperation, especially when the agents adopt the discriminator strategy. The adjustment of social links results in the formation of communities of “like-minded” agents. Subsequently, this local optimal behaviour promotes the evolution of cooperative behaviour at the system level.
Cholesterol, cancer, and rebooting a treatment for athlete's foot.
Chua, Ngee Kiat; Coates, Hudson W; Brown, Andrew J
2018-04-18
A key enzyme in cholesterol synthesis is placed firmly on the oncogenic map and demonstrated to be a potential therapeutic target in liver cancer by repurposing a common antifungal agent (Liu et al , this issue). Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Effects of reduced impact logging on bat biodiversity in terra firme forest of lowland Amazonia.
Ivan Castro-Arellanos; Steven J. Presley; Luis Nelio Saldanha; Michael R. Willig; Joseph M. Wunderle Jr.
2007-01-01
Timber harvest is one of the main causes of degradation of Amazonian tropical forests, where bats represent important components of biodiversity. In addition, bats may represent keystone taxa in the Neotropics, as they are primary agents of pollination and seed dispersal for many pioneer plants. We assessed the impact of low harvest (18m3/ha),...
Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A
2015-09-01
This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. © 2015 Society for Risk Analysis.
Performance improvement: an active life cycle product management
NASA Astrophysics Data System (ADS)
Cucchiella, Federica; Gastaldi, Massimo; Lenny Koh, S. C.
2010-03-01
The management of the supply chain has gained importance in many manufacturing firms. Operational flexibility can be considered a crucial weapon to increase competitiveness in a turbulent marketplace. It reflects the ability of a firm to properly and rapidly respond to a variable and dynamic environment. For the firm operating in a fashion sector, the management of the supply chain is even more complex because the product life cycle is shorter than that of the firm operating in a non-fashion sector. The increase of firm flexibility level can be reached through the application of the real option theory inside the firm network. In fact, real option may increase the project value by allowing managers to more efficiently direct the production. The real option application usually analysed in literature does not take into account that the demands of products are well-defined by the product life cycle. Working on a fashion sector, the life cycle pattern is even more relevant because of an expected demand that grows according to a constant rate that does not capture the demand dynamics of the underlying fashion goods. Thus, the primary research objective of this article is to develop a model useful for the management of investments in a supply chain operating in a fashion sector where the system complexity is increased by the low level of unpredictability and stability that is proper of the mood phenomenon. Moreover, unlike the traditional model, a real option framework is presented here that considers fashion product characterised by uncertain stages of the production cycle.
Kawamoto, Hirokazu; Takayasu, Hideki; Jensen, Henrik Jeldtoft; Takayasu, Misako
2015-01-01
Through precise numerical analysis, we reveal a new type of universal loopless percolation transition in randomly removed complex networks. As an example of a real-world network, we apply our analysis to a business relation network consisting of approximately 3,000,000 links among 300,000 firms and observe the transition with critical exponents close to the mean-field values taking into account the finite size effect. We focus on the largest cluster at the critical point, and introduce survival probability as a new measure characterizing the robustness of each node. We also discuss the relation between survival probability and k-shell decomposition. PMID:25885791
Absorptive capacity, technological innovation, and product life cycle: a system dynamics model.
Zou, Bo; Guo, Feng; Guo, Jinyu
2016-01-01
While past research has recognized the importance of the dynamic nature of absorptive capacity, there is limited knowledge on how to generate a fair and comprehensive analytical framework. Based on interviews with 24 Chinese firms, this study develops a system-dynamics model that incorporates an important feedback loop among absorptive capacity, technological innovation, and product life cycle (PLC). The simulation results reveal that (1) PLC affects the dynamic process of absorptive capacity; (2) the absorptive capacity of a firm peaks in the growth stage of PLC, and (3) the market demand at different PLC stages is the main driving force in firms' technological innovations. This study also explores a sensitivity simulation using the variables of (1) time spent in founding an external knowledge network, (2) research and development period, and (3) knowledge diversity. The sensitivity simulation results show that the changes of these three variables have a greater impact on absorptive capacity and technological innovation during growth and maturity stages than in the introduction and declining stages of PLC. We provide suggestions on how firms can adjust management policies to improve their absorptive capacity and technological innovation performance during different PLC stages.
Exploring the resilience of industrial ecosystems.
Zhu, Junming; Ruth, Matthias
2013-06-15
Industrial ecosystems improve eco-efficiency at the system level through optimizing material and energy flows, which however raises a concern for system resilience because efficiency, as traditionally conceived, not necessarily promotes resilience. By drawing on the concept of resilience in ecological systems and in supply chains, resilience in industrial ecosystems is specified on the basis of a system's ability to maintain eco-efficient material and energy flows under disruptions. Using a network model that captures supply, asset, and organizational dependencies and propagation of disruptions among firms, the resilience, and particularly resistance as an important dimension of resilience, of two real industrial ecosystems and generalized specifications are examined. The results show that an industrial ecosystem is less resistant and less resilient with high inter-firm dependency, preferentially organized physical exchanges, and under disruptions targeted at highly connected firms. An industrial ecosystem with more firms and exchanges is less resistant, but has more eco-efficient flows and potentials, and therefore is less likely to lose its function of eco-efficiency. Taking these determinants for resilience into consideration improves the adaptability of an industrial ecosystem, which helps increase its resilience. Copyright © 2013 Elsevier Ltd. All rights reserved.
Enterprise 2.0: An Extended Technology Acceptance Model
ERIC Educational Resources Information Center
Kurz, James M.
2012-01-01
The amount of information that people produce is changing, especially as social networking becomes more commonplace and globalization inefficiencies continue to swamp enterprise. Companies are rising to the challenge to create a collaborative approach for information management, but according to many leading technology advisory firms, they have…
The Future Is Kids and Computers.
ERIC Educational Resources Information Center
Personal Computing, 1982
1982-01-01
Describes a project which produced educational computer programs for PET microcomputers and use of computers in money management, in a filter company, and in a certified public accountant firm (which cancelled a contract for a time-sharing service). Also describes a computerized eye information network for ophthalmologists. (JN)
The National Information Infrastructure: Agenda for Action.
ERIC Educational Resources Information Center
Department of Commerce, Washington, DC. Information Infrastructure Task Force.
The National Information Infrastructure (NII) is planned as a web of communications networks, computers, databases, and consumer electronics that will put vast amounts of information at the users' fingertips. Private sector firms are beginning to develop this infrastructure, but essential roles remain for the Federal Government. The National…
Explaining Inference on a Population of Independent Agents Using Bayesian Networks
ERIC Educational Resources Information Center
Sutovsky, Peter
2013-01-01
The main goal of this research is to design, implement, and evaluate a novel explanation method, the hierarchical explanation method (HEM), for explaining Bayesian network (BN) inference when the network is modeling a population of conditionally independent agents, each of which is modeled as a subnetwork. For example, consider disease-outbreak…
Adaptivity in Agent-Based Routing for Data Networks
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Kirshner, Sergey; Merz, Chris J.; Turner, Kagan
2000-01-01
Adaptivity, both of the individual agents and of the interaction structure among the agents, seems indispensable for scaling up multi-agent systems (MAS s) in noisy environments. One important consideration in designing adaptive agents is choosing their action spaces to be as amenable as possible to machine learning techniques, especially to reinforcement learning (RL) techniques. One important way to have the interaction structure connecting agents itself be adaptive is to have the intentions and/or actions of the agents be in the input spaces of the other agents, much as in Stackelberg games. We consider both kinds of adaptivity in the design of a MAS to control network packet routing. We demonstrate on the OPNET event-driven network simulator the perhaps surprising fact that simply changing the action space of the agents to be better suited to RL can result in very large improvements in their potential performance: at their best settings, our learning-amenable router agents achieve throughputs up to three and one half times better than that of the standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol traffic is maintained. We then demonstrate that much of that potential improvement can be realized by having the agents learn their settings when the agent interaction structure is itself adaptive.
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.
A secure 3-way routing protocols for intermittently connected mobile ad hoc networks.
Sekaran, Ramesh; Parasuraman, Ganesh Kumar
2014-01-01
The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET.
A Secure 3-Way Routing Protocols for Intermittently Connected Mobile Ad Hoc Networks
Parasuraman, Ganesh Kumar
2014-01-01
The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET. PMID:25136697
NASA Astrophysics Data System (ADS)
Analoui, Morteza; Rezvani, Mohammad Hossein
2011-01-01
Behavior modeling has recently been investigated for designing self-organizing mechanisms in the context of communication networks in order to exploit the natural selfishness of the users with the goal of maximizing the overall utility. In strategic behavior modeling, the users of the network are assumed to be game players who seek to maximize their utility with taking into account the decisions that the other players might make. The essential difference between the aforementioned researches and this work is that it incorporates the non-strategic decisions in order to design the mechanism for the overlay network. In this solution concept, the decisions that a peer might make does not affect the actions of the other peers at all. The theory of consumer-firm developed in microeconomics is a model of the non-strategic behavior that we have adopted in our research. Based on it, we have presented distributed algorithms for peers' "joining" and "leaving" operations. We have modeled the overlay network as a competitive economy in which the content provided by an origin server can be viewed as commodity and the origin server and the peers who multicast the content to their downside are considered as the firms. On the other hand, due to the dual role of the peers in the overlay network, they can be considered as the consumers as well. On joining to the overlay economy, each peer is provided with an income and tries to get hold of the service regardless to the behavior of the other peers. We have designed the scalable algorithms in such a way that the existence of equilibrium price (known as Walrasian equilibrium price) is guaranteed.
Zubek, Julian; Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz
2017-01-01
This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems.
Denkiewicz, Michał; Barański, Juliusz; Wróblewski, Przemysław; Rączaszek-Leonardi, Joanna; Plewczynski, Dariusz
2017-01-01
This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. PMID:28809957
Aligning incentives in supply chains.
Narayanan, V G; Raman, Ananth
2004-11-01
Most companies don't worry about the behavior of their supply chain partners. Instead, they expect the supply chain to work efficiently without interference, as if guided by Adam Smith's famed invisible hand. In their study of more than 50 supply networks, V.G. Narayanan and Ananth Raman found that companies often looked out for their own interests and ignored those of their network partners. Consequently, supply chains performed poorly. Those results aren't shocking when you consider that supply chains extend across several functions and many companies, each with its own priorities and goals. Yet all those functions and firms must pull in the same direction for a chain to deliver goods and services to consumers quickly and cost-effectively. According to the authors, a supply chain works well only if the risks, costs, and rewards of doing business are distributed fairly across the network. In fact, misaligned incentives are often the cause of excess inventory, stock-outs, incorrect forecasts, inadequate sales efforts, and even poor customer service. The fates of all supply chain partners are interlinked: If the firms work together to serve consumers, they will all win. However, they can do that only if incentives are aligned. Companies must acknowledge that the problem of incentive misalignment exists and then determine its root cause and align or redesign incentives. They can improve alignment by, for instance, adopting revenue-sharing contracts, using technology to track previously hidden information, or working with intermediaries to build trust among network partners. It's also important to periodically reassess incentives, because even top-performing networks find that changes in technology or business conditions alter the alignment of incentives.
Studies of Opinion Stability for Small Dynamic Networks with Opportunistic Agents
NASA Astrophysics Data System (ADS)
Sobkowicz, Pawel
There are numerous examples of societies with extremely stable mix of contrasting opinions. We argue that this stability is a result of an interplay between society network topology adjustment and opinion changing processes. To support this position we present a computer model of opinion formation based on some novel assumptions, designed to bring the model closer to social reality. In our model, the agents, in addition to changing their opinions due to influence of the rest of society and external propaganda, have the ability to modify their social network, forming links with agents sharing the same opinions and cutting the links with those they disagree with. To improve the model further we divide the agents into "fanatics" and "opportunists," depending on how easy it is to change their opinions. The simulations show significant differences compared to traditional models, where network links are static. In particular, for the dynamical model where inter-agent links are adjustable, the final network structure and opinion distribution is shown to resemble real world observations, such as social structures and persistence of minority groups even when most of the society is against them and the propaganda is strong.
The Importance and Satisfaction of Collaborative Innovation for Strategic Entrepreneurship
ERIC Educational Resources Information Center
Tsai, I-Chang; Lei, Han-Sheng
2016-01-01
Building on network, learning, resource-based and real options theories, collaborative innovation through the sharing of ideas, knowledge, expertise, and opportunities can enable both small and large firms to successfully engage in strategic entrepreneurship. We use the real case of a research-oriented organization and its incubator for analysis…
Re-conceptualsing Learning Spaces: Developing Capabilities in a High-Tech Small Firm.
ERIC Educational Resources Information Center
Macpherson, Allan; Jones, Ossie; Zhang, Michael; Wilson, Alison
2003-01-01
A case study of a small high-tech business explains how they created a virtual cluster of innovation through supply networks, enhancing their own learning and facilitating integration of knowledge. This process overcomes limitations to management learning for small companies in isolated regions. (Contains 66 references.) (SK)
Supplier Relationships and Training. Contractor Report.
ERIC Educational Resources Information Center
Tornatzky, Louis G.; And Others
A study was undertaken to describe how changes in the network of transactions that occur between manufacturers and suppliers have affected the scope and nature of training and related human resource practices within supplier firms. Data came from the published literature, expert opinion, and a phone survey of 15 individuals ranging from…
Leveraging the Talent-Driven Organization
ERIC Educational Resources Information Center
Adler, Richard
2010-01-01
This report details how a number of firms are using social networking tools to open up communication, collaboration and learning across boundaries, leveraging these tools to develop new products and real-time solutions for customers. It discusses the qualities of leadership throughout an organization that fosters innovation and learning. And it…
Networked Success and Failure at Hybritech
ERIC Educational Resources Information Center
Jones, Mark Peter
2011-01-01
The author presents an historical account of scientific work conducted at a commercial biotech firm in San Diego called Hybritech. It tells of disruptions in research programs following the acquisition of the company by the pharmaceutical giant Eli Lilly in 1986. The story centers on responses to an organizational challenge that research managers…
Exploiting Terrorist Vulnerabilities: A Law Enforcement Approach to Fighting Terrorist Organizations
2009-05-01
assassination led to a crackdown by the Egyptian Government. This crackdown led to an alliance with Gamal Abdel Nasser. Nasser promised a return to......He believed that the Western powers were bleeding Egyptian resources dry. He was firmly against capitalism and formed a social welfare network
A Decentralized Framework for Multi-Agent Robotic Systems
2018-01-01
Over the past few years, decentralization of multi-agent robotic systems has become an important research area. These systems do not depend on a central control unit, which enables the control and assignment of distributed, asynchronous and robust tasks. However, in some cases, the network communication process between robotic agents is overlooked, and this creates a dependency for each agent to maintain a permanent link with nearby units to be able to fulfill its goals. This article describes a communication framework, where each agent in the system can leave the network or accept new connections, sending its information based on the transfer history of all nodes in the network. To this end, each agent needs to comply with four processes to participate in the system, plus a fifth process for data transfer to the nearest nodes that is based on Received Signal Strength Indicator (RSSI) and data history. To validate this framework, we use differential robotic agents and a monitoring agent to generate a topological map of an environment with the presence of obstacles. PMID:29389849
Adaptation and survivors in a random Boolean network.
Nakamura, Ikuo
2002-04-01
We introduce the competitive agent with imitation strategy in a random Boolean network, in which the agent plays a competitive game that rewards those in minority. After a long time interval, the worst performer changes its strategy to the one of the best and the process is repeated. The network, initially in a chaotic state, evolves to an intermittent state and finally reaches a frozen state. Time series of survived species (whose strategies are imitated by other agents) in the system depend on the connectivity of each agent. In a system with various connectivity groups, the low connectivity groups win the minority game over the high connectivity groups. We also compared the result with mutation strategy system.
Transition to parenthood: the role of social interaction and endogenous networks.
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.
Using an agent-based model to analyze the dynamic communication network of the immune response
2011-01-01
Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win) versus persistent infection (loss), due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the loss outcomes. Conclusions An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies. PMID:21247471
Chin, Tachia; Tsai, Sang-Bing; Fang, Kai; Zhu, Wenzhong; Yang, Dongjin; Liu, Ren-Huai; Tsuei, Richard Ting Chang
2016-01-01
Due to the context-sensitive nature of entrepreneurial orientation (EO), it is imperative to in-depth explore the EO-performance mechanism in China at its critical, specific stage of economic reform. Under the context of "reverse internationalization" by Chinese global startup original equipment manufacturers (OEMs), this paper aims to manifest the unique links and complicated interrelationships between the individual EO dimensions and firm performance. Using structural equation modeling, we found that during reverse internationalization, proactiveness is positively related to performance; risk taking is not statistically associated with performance; innovativeness is negatively related to performance. The proactiveness-performance relationship is mediated by Strategic flexibility and moderated by social networking relationships. The dynamic and complex institutional setting, coupled with the issues of overcapacity and rising labor cost in China may explain why our distinctive results occur. This research advances the understanding of how contingent factors (social network relationships and strategic flexibility) facilitate entrepreneurial firms to break down institutional barriers and reap the most from EO. It brings new insights into how Chinese global startup OEMs draw on EO to undertake reverse internationalization, responding the calls for unraveling the heterogeneous characteristics of EO sub-dimensions and for more contextually-embedded treatment of EO-performance associations.
Chin, Tachia; Tsai, Sang-Bing; Fang, Kai; Zhu, Wenzhong; Yang, Dongjin; Liu, Ren-huai; Tsuei, Richard Ting Chang
2016-01-01
Due to the context-sensitive nature of entrepreneurial orientation (EO), it is imperative to in-depth explore the EO-performance mechanism in China at its critical, specific stage of economic reform. Under the context of “reverse internationalization” by Chinese global startup original equipment manufacturers (OEMs), this paper aims to manifest the unique links and complicated interrelationships between the individual EO dimensions and firm performance. Using structural equation modeling, we found that during reverse internationalization, proactiveness is positively related to performance; risk taking is not statistically associated with performance; innovativeness is negatively related to performance. The proactiveness-performance relationship is mediated by Strategic flexibility and moderated by social networking relationships. The dynamic and complex institutional setting, coupled with the issues of overcapacity and rising labor cost in China may explain why our distinctive results occur. This research advances the understanding of how contingent factors (social network relationships and strategic flexibility) facilitate entrepreneurial firms to break down institutional barriers and reap the most from EO. It brings new insights into how Chinese global startup OEMs draw on EO to undertake reverse internationalization, responding the calls for unraveling the heterogeneous characteristics of EO sub-dimensions and for more contextually-embedded treatment of EO-performance associations. PMID:27631368
Li, Huaqing; Chen, Guo; Huang, Tingwen; Dong, Zhaoyang; Zhu, Wei; Gao, Lan
2016-12-01
In this paper, we consider the event-triggered distributed average-consensus of discrete-time first-order multiagent systems with limited communication data rate and general directed network topology. In the framework of digital communication network, each agent has a real-valued state but can only exchange finite-bit binary symbolic data sequence with its neighborhood agents at each time step due to the digital communication channels with energy constraints. Novel event-triggered dynamic encoder and decoder for each agent are designed, based on which a distributed control algorithm is proposed. A scheme that selects the number of channel quantization level (number of bits) at each time step is developed, under which all the quantizers in the network are never saturated. The convergence rate of consensus is explicitly characterized, which is related to the scale of network, the maximum degree of nodes, the network structure, the scaling function, the quantization interval, the initial states of agents, the control gain and the event gain. It is also found that under the designed event-triggered protocol, by selecting suitable parameters, for any directed digital network containing a spanning tree, the distributed average consensus can be always achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step. Two simulation examples are provided to illustrate the feasibility of presented protocol and the correctness of the theoretical results.
Intrinsic motivation and organizational identification among on-demand workers.
Rockmann, Kevin W; Ballinger, Gary A
2017-09-01
On-demand firms provide services for clients through a network of on-demand workers ready to complete specific tasks for a set contractual price. Given such on-demand work is defined by payment on short-term contracts with no obligation for continued employment, there is little reason to believe on-demand workers experience more than extrinsic motivation and a transactional relationship with the on-demand firm. However, using self-determination theory, we argue that to the degree that on-demand work fulfills innate psychological needs individual on-demand workers will develop intrinsic motivation, which further leads to organizational identification with the on-demand firm. Across 2 survey-based studies we find support for this path to organizational identification. This adds to the literature on motivation and identification by strengthening the link between individual needs and the individual-organizational relationship. Implications for theory and for the management of on-demand workers are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Miyamoto, Ryoma; Utano, Tatsumi; Yasuhara, Shunya; Ishihara, Shota; Ohshima, Masahiro
2015-05-01
In this study, the core-back foam injection molding was used for preparing microcelluar polypropylene (PP) foam with either a 1,3:2,4 bis-O-(4-methylbenzylidene)-D-sorbitol gelling agent (Gel-all MD) or a fibros network polymer additive (Metablen 3000). Both agent and addiive could effectively control the celluar morphology in foams but somehow different ways. In course of cooling the polymer with Gel-all MD in the mold caity, the agent enhanced the crystal nucleation and resulted in the large number of small crystals. The crystals acted as effective bubble nucleation agent in foaming process. Thus, the agent reduced the cell size and increased the cell density, drastically. Furthermore, the small crystals provided an inhomogenuity to the expanding cell wall and produced the high open cell content with nano-scale fibril structure. Gell-all as well as Metablene 3000 formed a gel-like fibrous network in melt. The network increased the elongational viscosity and tended to prevent the cell wall from breaking up. The foaming temperature window was widened by the presence of the network. Especially, the temperature window where the macro-fibrous structure was formed was expanded to the higher temperature. The effects of crystal nucleating agent and PTFE on crystals' size and number, viscoelsticity, rheological propreties of PP and cellular morphology were compared and thorougly investigated.
NASA Astrophysics Data System (ADS)
Patil, Riya Raghuvir
Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for selfpartitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the LegoRTM Mindstorms' NXT on a graphical programming platform using National Instruments' LabVIEW(TM) forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.
Evolutionary Games in Multi-Agent Systems of Weighted Social Networks
NASA Astrophysics Data System (ADS)
Du, Wen-Bo; Cao, Xian-Bin; Zheng, Hao-Ran; Zhou, Hong; Hu, Mao-Bin
Much empirical evidence has shown realistic networks are weighted. Compared with those on unweighted networks, the dynamics on weighted network often exhibit distinctly different phenomena. In this paper, we investigate the evolutionary game dynamics (prisoner's dilemma game and snowdrift game) on a weighted social network consisted of rational agents and focus on the evolution of cooperation in the system. Simulation results show that the cooperation level is strongly affected by the weighted nature of the network. Moreover, the variation of time series has also been investigated. Our work may be helpful in understanding the cooperative behavior in the social systems.
Wiltshire, Serge W
2018-01-01
An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents' contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments-defined by one-phase, two-phase, and three-phase production systems-a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer-producer edges may be largely responsible for the superior disease resilience of single-phase "farrow to finish" production systems.
Communication Policies in Knowledge Networks
NASA Astrophysics Data System (ADS)
Ioannidis, Evangelos; Varsakelis, Nikos; Antoniou, Ioannis
2018-02-01
Faster knowledge attainment within organizations leads to improved innovation, and therefore competitive advantage. Interventions on the organizational network may be risky or costly or time-demanding. We investigate several communication policies in knowledge networks, which reduce the knowledge attainment time without interventions. We examine the resulting knowledge dynamics for real organizational networks, as well as for artificial networks. More specifically, we investigate the dependence of knowledge dynamics on: (1) the Selection Rule of agents for knowledge acquisition, and (2) the Order of implementation of "Selection" and "Filtering". Significant decrease of the knowledge attainment time (up to -74%) can be achieved by: (1) selecting agents of both high knowledge level and high knowledge transfer efficiency, and (2) implementing "Selection" after "Filtering" in contrast to the converse, implicitly assumed, conventional prioritization. The Non-Commutativity of "Selection" and "Filtering", reveals a Non-Boolean Logic of the Network Operations. The results demonstrate that significant improvement of knowledge dynamics can be achieved by implementing "fruitful" communication policies, by raising the awareness of agents, without any intervention on the network structure.
An enhanced performance through agent-based secure approach for mobile ad hoc networks
NASA Astrophysics Data System (ADS)
Bisen, Dhananjay; Sharma, Sanjeev
2018-01-01
This paper proposes an agent-based secure enhanced performance approach (AB-SEP) for mobile ad hoc network. In this approach, agent nodes are selected through optimal node reliability as a factor. This factor is calculated on the basis of node performance features such as degree difference, normalised distance value, energy level, mobility and optimal hello interval of node. After selection of agent nodes, a procedure of malicious behaviour detection is performed using fuzzy-based secure architecture (FBSA). To evaluate the performance of the proposed approach, comparative analysis is done with conventional schemes using performance parameters such as packet delivery ratio, throughput, total packet forwarding, network overhead, end-to-end delay and percentage of malicious detection.
Opinion formation of free speech on the directed social network
NASA Astrophysics Data System (ADS)
Su, Jiongming; Ma, Hongxu; Liu, Baohong; Li, Qi
2014-12-01
A dynamical model with continuous opinion is proposed to study how the speech order and the topology of directed social network affect the opinion formation of free speech. In the model, agents express their opinions one by one with random order (RO) or probability order (PO), other agents paying attentions to the speaking agent, receive provider's opinion, update their opinions and then express their new opinions in their turns. It is proved that with the same agent j repeats its opinion more, other agents who pay their attentions to j and include j's opinion in their confidence level at initial time, will continue approaching j's opinion. Simulation results reveal that on directed scale-free network: (1) the model for PO forms fewer opinion clusters, larger maximum cluster (MC), smaller standard deviation (SD), and needs less waiting time to reach a middle level of consensus than RO; (2) as the parameter of scale-free degree distribution decreases or the confidence level increases, the results often get better for both speech orders; (3) the differences between PO and RO get smaller as the size of network decreases.
Celestial data routing network
NASA Astrophysics Data System (ADS)
Bordetsky, Alex
2000-11-01
Imagine that information processing human-machine network is threatened in a particular part of the world. Suppose that an anticipated threat of physical attacks could lead to disruption of telecommunications network management infrastructure and access capabilities for small geographically distributed groups engaged in collaborative operations. Suppose that small group of astronauts are exploring the solar planet and need to quickly configure orbital information network to support their collaborative work and local communications. The critical need in both scenarios would be a set of low-cost means of small team celestial networking. To the geographically distributed mobile collaborating groups such means would allow to maintain collaborative multipoint work, set up orbital local area network, and provide orbital intranet communications. This would be accomplished by dynamically assembling the network enabling infrastructure of the small satellite based router, satellite based Codec, and set of satellite based intelligent management agents. Cooperating single function pico satellites, acting as agents and personal switching devices together would represent self-organizing intelligent orbital network of cooperating mobile management nodes. Cooperative behavior of the pico satellite based agents would be achieved by comprising a small orbital artificial neural network capable of learning and restructing the networking resources in response to the anticipated threat.
Impact of mobility structure on optimization of small-world networks of mobile agents
NASA Astrophysics Data System (ADS)
Lee, Eun; Holme, Petter
2016-06-01
In ad hoc wireless networking, units are connected to each other rather than to a central, fixed, infrastructure. Constructing and maintaining such networks create several trade-off problems between robustness, communication speed, power consumption, etc., that bridges engineering, computer science and the physics of complex systems. In this work, we address the role of mobility patterns of the agents on the optimal tuning of a small-world type network construction method. By this method, the network is updated periodically and held static between the updates. We investigate the optimal updating times for different scenarios of the movement of agents (modeling, for example, the fat-tailed trip distances, and periodicities, of human travel). We find that these mobility patterns affect the power consumption in non-trivial ways and discuss how these effects can best be handled.
Lopes, António Luís; Botelho, Luís Miguel
2013-01-01
In this paper, we describe a distributed coordination system that allows agents to seamlessly cooperate in problem solving by partially contributing to a problem solution and delegating the subproblems for which they do not have the required skills or knowledge to appropriate agents. The coordination mechanism relies on a dynamically built semantic overlay network that allows the agents to efficiently locate, even in very large unstructured networks, the necessary skills for a specific problem. Each agent performs partial contributions to the problem solution using a new distributed goal-directed version of the Graphplan algorithm. This new goal-directed version of the original Graphplan algorithm provides an efficient solution to the problem of "distraction", which most forward-chaining algorithms suffer from. We also discuss a set of heuristics to be used in the backward-search process of the planning algorithm in order to distribute this process amongst idle agents in an attempt to find a solution in less time. The evaluation results show that our approach is effective in building a scalable and efficient agent society capable of solving complex distributable problems. PMID:23704885
Employer-provided health insurance and hospital mergers.
Garmon, Christopher
2013-07-01
This paper explores the impact of employer-provided health insurance on hospital competition and hospital mergers. Under employer-provided health insurance, employer executives act as agents for their employees in selecting health insurance options for their firm. The paper investigates whether a merger of hospitals favored by executives will result in a larger price increase than a merger of competing hospitals elsewhere. This is found to be the case even when the executive has the same opportunity cost of travel as her employees and even when the executive is the sole owner of the firm, retaining all profits. This is consistent with the Federal Trade Commission's findings in its challenge of Evanston Northwestern Healthcare's acquisition of Highland Park Hospital. Implications of the model are further tested with executive location data and hospital data from Florida and Texas.
NASA Technical Reports Server (NTRS)
White, J.; Gaines, D. M.; Wilkes, M.; Kusumalnukool, K.; Thongchai, S.; Kawamura, K.
2001-01-01
This approach provides the agent with a causal structure, the spreading activation network, relating goals to the actions that can achieve those goals. This enables the agent to select actions relative to the goal priorities.
Agreement dynamics on interaction networks with diverse topologies
NASA Astrophysics Data System (ADS)
Barrat, Alain; Baronchelli, Andrea; Dall'Asta, Luca; Loreto, Vittorio
2007-06-01
We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence.
NASA Astrophysics Data System (ADS)
Park, Sangsoo; Miura, Yushi; Ise, Toshifumi
This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.
Electronic Field Data Collection in Support of Satellite-Based Food Security Monitoring in Tanzania
NASA Astrophysics Data System (ADS)
Nakalembe, C. L.; Dempewolf, J.; Justice, C. J.; Becker-Reshef, I.; Tumbo, S.; Maurice, S.; Mbilinyi, B.; Ibrahim, K.; Materu, S.
2016-12-01
In Tanzania agricultural extension agents traditionally collect field data on agriculture and food security on paper, covering most villages throughout the country. The process is expensive, slow and cumbersome and prone to data transcription errors when the data get entered at the district offices into electronic spreadsheets. Field data on the status and condition of agricultural crops, the population's nutritional status, food storage levels and other parameters are needed in near realtime for early warning to make critical but most importantly timely and appropriate decisions that are informed with verified data from the ground. With the ubiquitous distribution of cell phones, which are now used by the vast majority of the population in Tanzania including most farmers, new, efficient and cost-effective methods for field data collection have become available. Using smartphones and tablets data on crop conditions, pest and diseases, natural disasters and livelihoods can be collected and made available and easily accessible in near realtime. In this project we implemented a process for obtaining high quality electronic field data using the GeoODK application with a large network of field extension agents in Tanzania and Uganda. These efforts contribute to work being done on developing an advanced agriculture monitoring system for Tanzania, incorporating traditional data collection with satellite information and field data. The outcomes feed directly into the National Food Security Bulletin for Tanzania produced by the Ministry of Agriculture as well as a form a firm evidence base and field scale monitoring of the disaster risk financing in Uganda.
Las estrategias de un lider (The Strategies of a Leader). ERIC Digest.
ERIC Educational Resources Information Center
Lashway, Larry
A decade ago, principals were asked to become instructional leaders who exercised firm control by setting goals, maintaining discipline, and evaluating results. Today, they are encouraged to act as facilitative leaders by building teams, creating networks, and "governing from the center." Rapid shifts in administrative philosophy can be…
ERIC Educational Resources Information Center
Villano, Matt; Gullon, Monica
2009-01-01
Like fine wines, Web 2.0 technologies get better with age. Gone are the days of the pointless chat room; this is the era of social networking juggernauts such as Facebook, MySpace, and Friendster. Services offered by these firms are helpful in facilitating connections among users in every industry and of every age. In higher education, however, a…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-05
... Science Center's Social Sciences Branch seeks to collect data on distribution networks and business... also seeks to collect data on business disruptions due to Hurricane Sandy for those firms. The data collected will improve research and analysis on the economic impacts of potential fishery management actions...
Business Value of Information Technology in Network Environments
ERIC Educational Resources Information Center
Liu, Yucong
2012-01-01
Information Technology (IT) business value research is suggested as fundamental to the contribution of the IS discipline. The IS research community has accumulated a critical mass of IT business value studies, but only limited or mixed results have been found on the direct relationship between IT and firm performance. Extant studies mostly focus…
Essays on Innovation Ecosystems in the Enterprise Software Industry
ERIC Educational Resources Information Center
Huang, Peng
2010-01-01
Innovation ecosystem strategy is often adopted by platform technology owners to seek complementary innovation from resources located outside the firm to exploit indirect network effect. In this dissertation I aim to address the issues that are related to the formation and business value of platform innovation ecosystems in the enterprise software…
Software Innovations: The Influence of Quality, Diversity and Structure of Network Ties
ERIC Educational Resources Information Center
Singh, Harpeet
2010-01-01
There is high uncertainty associated with the outcomes of Information Technology (IT) investments and innovations. In such environments, IT actors (firm and individuals) are also unsure about their actions and preferences. The social relationships of these actors create substantial value for these actors in multiple ways (e.g. providing social…
Essays on Adoption and Diffusion of New Technology in Supply Chains
ERIC Educational Resources Information Center
Choi, Daeheon
2012-01-01
Over the past decades, network technologies across supply chains have been introduced and promoted with the premised benefits for all participants. However industry experience with an adoption process of some technology suggests that some firms have a great amount of uncertainty in estimating the benefits of its adoption. This uncertainty will…
Regimes of Performance: Practices of the Normalised Self in the Neoliberal University
ERIC Educational Resources Information Center
Morrissey, John
2015-01-01
Universities today inescapably find themselves part of nationally and globally competitive networks that appear firmly inflected by neoliberal concerns of rankings, benchmarking and productivity. This, of course, has in turn led to progressively anticipated and regulated forms of academic subjectivity that many fear are overly econo-centric in…
The Effectiveness of Knowledge Networks: An Investigation of Manufacturing SMEs
ERIC Educational Resources Information Center
Hughes, Tim; O'Regan, Nicholas; Sims, Martin A.
2009-01-01
Purpose: Although considerable attention in the extant literature has been devoted to knowledge acquisition and transfer within firms, there is a dearth of research on the effectiveness of outside sources of knowledge for technology-based small to medium-sized enterprises (SMEs). Furthermore, the majority of empirical studies in this area focus on…
Learning-by-Doing in Transnational Operations Networks: Insights from Economic Geography
ERIC Educational Resources Information Center
Spring, Martin
2006-01-01
Purpose: The purpose of this paper is to explore how insights from economic geography, which are typically explanatory or directed at policy prescription, might be utilized to provide managerial insight at firm level into the processes of and conditions for tacit knowledge transfer. Design/methodology/approach: This is a theoretical paper. The…
Cognitive conflict without explicit conflict monitoring in a dynamical agent.
Ward, Robert; Ward, Ronnie
2006-11-01
We examine mechanisms for resolving cognitive conflict in an embodied, situated, and dynamic agent, developed through an evolutionary learning process. The agent was required to solve problems of response conflict in a dual-target "catching" task, focusing response on one of the targets while ignoring the other. Conflict in the agent was revealed at the behavioral level in terms of increased latencies to the second target. This behavioral interference was correlated to peak violations of the network's stable state equation. At the level of the agent's neural network, peak violations were also correlated to periods of disagreement in source inputs to the agent's motor effectors. Despite observing conflict at these numerous levels, we did not find any explicit conflict monitoring mechanisms within the agent. We instead found evidence of a distributed conflict management system, characterized by competitive sources within the network. In contrast to the conflict monitoring hypothesis [Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108(3), 624-652], this agent demonstrates that resolution of cognitive conflict does not require explicit conflict monitoring. We consider the implications of our results for the conflict monitoring hypothesis.
Medicine or ecstasy? The importance of the logo.
Daveluy, Amélie; Miremont-Salamé, Ghada; Rahis, Anne-Cécile; Delile, Jean-Michel; Bégaud, Bernard; Gachie, Jean-Pierre; Haramburu, Françoise
2010-04-01
Some pharmaceutical tablets have an appearance that resembles that of ecstasy (a logo and often a name referring to it, a given shape and/or a colour). These are sometimes sold in the street as 'ecstasy'. In order to assess the knowledge of this phenomenon, surveys were conducted among designer drug users (DDUsers), pharmacists and pharmaceutical firms. Three surveys were conducted: the first one was conducted among DDUsers by means of an anonymous questionnaire; the second one consisted of a 1-month postal survey within a network of 155 community pharmacies in the Aquitaine region, Southwestern France and the third one consisted of a postal questionnaire sent to 71 pharmaceutical firms. Nineteen users, 77 pharmacists and 25 pharmaceutical firms participated in the surveys. All DDUsers knew the existence of what they call ecstasy 'swindles', but less than one quarter of the pharmacists and one third of pharmaceutical firms were aware of the potential recreational and involuntary misuse of medicines. The phenomenon of 'swindle' in the illicit market is not new. However, the sale of medicines because of their appearance or logo seems to be quite rare. In order to limit this diversion, prevention should be reinforced. In addition, recommendations on the appearance of medicine tablets should be set up by regulatory agencies in charge of medicine approval.
Geographical influences of an emerging network of gang rivalries
NASA Astrophysics Data System (ADS)
Hegemann, Rachel A.; Smith, Laura M.; Barbaro, Alethea B. T.; Bertozzi, Andrea L.; Reid, Shannon E.; Tita, George E.
2011-10-01
We propose an agent-based model to simulate the creation of street gang rivalries. The movement dynamics of agents are coupled to an evolving network of gang rivalries, which is determined by previous interactions among agents in the system. Basic gang data, geographic information, and behavioral dynamics suggested by the criminology literature are integrated into the model. The major highways, rivers, and the locations of gangs’ centers of activity influence the agents’ motion. We use a policing division of the Los Angeles Police Department as a case study to test our model. We apply common metrics from graph theory to analyze our model, comparing networks produced by our simulations and an instance of a Geographical Threshold Graph to the existing network from the criminology literature.
Ownership strategies of multinational corporations: Towards designing effective global networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Raghunathan, S.P.
1992-01-01
The thesis of this research is that MNCs, attempting to implement different international strategies in response to several environmental factors, let their global networks evolve. The ownership structure of the network is therefore a function of the international strategy and environment of a firm. A particular strategy (configuration/coordination), given a certain environment, may be effective if associated with the appropriate structure. This study is based on a survey of 318 US manufacturing-sector MNCs using a questionnaire. The ownership structure of an MNC network was identified by studying the nature of ownership - method and form - of overseas subsidiaries. Usingmore » network theoretic methods, ownership structure was empirically related to international environment, strategy, and performance. Results of this study throw light on the design of global networks and enable a general theory of the design of MNCs to be eventually developed.« less
Tavares Estevam, Adriana Carneiro; de Almeida, Michele Correia; de Oliveira, Tiago Almeida; Florentino, Eliane Rolim; Alonso Buriti, Flávia Carolina; Porto, Ana Lúcia Figueiredo
2017-09-20
Dairy desserts have emerged as interesting options for the incorporation of probiotics, bioactive ingredients and alternative sources of thickeners. This shows an opportunity to investigate the use of Gracilaria seaweeds in the formulation of potentially probiotic dairy desserts. This study aimed to compare the effects of dispersions obtained from Gracilaria domingensis and Gracilaria birdiae used as thickening agents on texture properties of dairy desserts fermented with SAB 440-A, composed of the starter Streptococcus thermophilus and the potential probiotics Bifidobacterium animalis and Lactobacillus acidophilus, and also to study their physicochemical characteristics, microbial viability and sensory acceptability. No significant differences between desserts with G. birdiae or G. domingensis dispersions regarding total solids, ash and fat content, as well as pH, titratable acidity, the viability of the microorganisms of the mixed culture and sensory acceptability were verified (P > 0.05). Nonetheless, the dessert with G. domingensis dispersion showed higher dietary fibre content and significantly increased firmness than the one produced with G. birdiae (P < 0.05). Moreover, B. animalis was able to maintain higher populations, above 7 log cfu g -1 during 21 days of storage of desserts, in the presence of either G. birdiae or G. domingensis dispersions, despite the fact that L. acidophilus has shown low viability in the final products. Therefore, the G. domingensis dispersion is suitable to be used as a thickening agent to produce dairy desserts with enhanced firmness and good sensory acceptability, it being also advisable to use only B. animalis as a probiotic for this product.
NASA Astrophysics Data System (ADS)
Kurmyshev, Evguenii; Juárez, Héctor A.; González-Silva, Ricardo A.
2011-08-01
Bounded confidence models of opinion dynamics in social networks have been actively studied in recent years, in particular, opinion formation and extremism propagation along with other aspects of social dynamics. In this work, after an analysis of limitations of the Deffuant-Weisbuch (DW) bounded confidence, relative agreement model, we propose the mixed model that takes into account two psychological types of individuals. Concord agents (C-agents) are friendly people; they interact in a way that their opinions always get closer. Agents of the other psychological type show partial antagonism in their interaction (PA-agents). Opinion dynamics in heterogeneous social groups, consisting of agents of the two types, was studied on different social networks: Erdös-Rényi random graphs, small-world networks and complete graphs. Limit cases of the mixed model, pure C- and PA-societies, were also studied. We found that group opinion formation is, qualitatively, almost independent of the topology of networks used in this work. Opinion fragmentation, polarization and consensus are observed in the mixed model at different proportions of PA- and C-agents, depending on the value of initial opinion tolerance of agents. As for the opinion formation and arising of “dissidents”, the opinion dynamics of the C-agents society was found to be similar to that of the DW model, except for the rate of opinion convergence. Nevertheless, mixed societies showed dynamics and bifurcation patterns notably different to those of the DW model. The influence of biased initial conditions over opinion formation in heterogeneous social groups was also studied versus the initial value of opinion uncertainty, varying the proportion of the PA- to C-agents. Bifurcation diagrams showed an impressive evolution of collective opinion, in particular, radical changes of left to right consensus or vice versa at an opinion uncertainty value equal to 0.7 in the model with the PA/C mixture of population near 50/50.
Apparatus and Methods Using Highly Optically Dispersive Media
2011-08-02
University ; Sep. 24, 2001. * cited by examiner Primary Examiner- Michael A Lyons (74) Attorney , Agent, or Firm- William J. Greener; Bond...NY (US); Daniel J. Gauthier, Durham, NC (US); Zhimin Shi, Rochester, NY (US) (73) Assignees: University of Rochester, Rochester, NY (US); Duke... University , Durham, NC (US) ( *) Notice: Subject to any disclaimer, the term of this patent is extended or adjusted under 35 U.S.C. 154(b) by 250
Mobile Router Developed and Tested
NASA Technical Reports Server (NTRS)
Ivancic, William D.
2002-01-01
The NASA Glenn Research Center, under a NASA Space Act Agreement with Cisco Systems, has been performing joint networking research to apply Internet-based technologies and protocols to space-based communications. As a result of this research, NASA performed stringent performance testing of the mobile router, including the interaction of routing and the transport-level protocol. In addition, Cisco Systems developed the mobile router for both commercial and Government markets. The code has become part of the Cisco Systems Internetworking Operating System (IOS) as of release 12.2 (4) T--which will make this capability available to the community at large. The mobile router is software code that resides in a network router and enables entire networks to roam while maintaining connectivity to the Internet. This router code is pertinent to a myriad of applications for both Government and commercial sectors, including the "wireless battlefield." NASA and the Department of Defense will utilize this technology for near-planetary observation and sensing spacecraft. It is also a key enabling technology for aviation-based information applications. Mobile routing will make it possible for information such as weather, air traffic control, voice, and video to be transmitted to aircraft using Internet-based protocols. This technology shows great promise in reducing congested airways and mitigating aviation disasters due to bad weather. The mobile router can also be incorporated into emergency vehicles (such as ambulances and life-flight aircraft) to provide real-time connectivity back to the hospital and health-care experts, enabling the timely application of emergency care. Commercial applications include entertainment services, Internet protocol (IP) telephone, and Internet connectivity for cruise ships, commercial shipping, tour buses, aircraft, and eventually cars. A mobile router, which is based on mobile IP, allows hosts (mobile nodes) to seamlessly "roam" among various IP subnetworks. This is essential in many wireless networks. A mobile router, unlike a mobile IP node, allows entire networks to roam. Hence, a device connected to the mobile router does not need to be a mobile node because the mobile router provides the roaming capabilities. There are three basic elements in the mobile IP: the home agent, the foreign agent, and the mobile node. The home agent is a router on a mobile node's home network that tunnels datagrams for delivery to the mobile node when it is away from home. The foreign agent is a router on a remote network that provides routing services to a registered mobile node. The mobile node is a host or router that changes its point of attachment from one network or subnetwork to another. In mobile routing, virtual communications are maintained by the home agent, which forwards all packets for the mobile networks to the foreign agent. The foreign agent passes the packets to the mobile router, which then forwards the packets to the devices on its networks. As the mobile router moves, it will register with its home agent on its whereabouts via the foreign agent to assure continuous connectivity.
Robust Architectures for Complex Multi-Agent Heterogeneous Systems
2014-07-23
establish the tradeoff between the control performance and the QoS of the communications network . We also derived the performance bound on the difference...accomplished within this time period leveraged the prior accomplishments in the area of networked multi-agent systems. The past work (prior to 2011...distributed control of uncertain networked systems [3]. Additionally, a preliminary collision avoidance algorithm has been developed for a team of
NASA Astrophysics Data System (ADS)
Tanimoto, Jun
2013-07-01
Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner’s dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents’ strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents’ enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.
Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping
2015-01-01
Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China.
Jin, Yonghong; Zhang, Qi; Shan, Lifei; Li, Sai-Ping
2015-01-01
Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China. PMID:26340555
Effects of global financial crisis on network structure in a local stock market
NASA Astrophysics Data System (ADS)
Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo
2014-08-01
This study considers the effects of the 2008 global financial crisis on threshold networks of a local Korean financial market around the time of the crisis. Prices of individual stocks belonging to KOSPI 200 (Korea Composite Stock Price Index 200) are considered for three time periods, namely before, during, and after the crisis. Threshold networks are constructed from fully connected cross-correlation networks, and thresholds of cross-correlation coefficients are assigned to obtain threshold networks. At the high threshold, only one large cluster consisting of firms in the financial sector, heavy industry, and construction is observed during the crisis. However, before and after the crisis, there are several fragmented clusters belonging to various sectors. The power law of the degree distribution in threshold networks is observed within the limited range of thresholds. Threshold networks are fatter during the crisis than before or after the crisis. The clustering coefficient of the threshold network follows the power law in the scaling range.
Optimization-Based Selection of Influential Agents in a Rural Afghan Social Network
2010-06-01
nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent assignment strategy producing the greatest...leader social network, and 3) the nonlethal targeting model, a nonlinear programming ( NLP ) optimization formulation that identifies the k US agent...NATO Coalition in Afghanistan. 55 for Afghanistan ( [54], [31], [48], [55], [30]). While Arab tribes tend to be more hierarchical, Pashtun tribes are
Nagendran, Myura; Maruthappu, Mahiben; Gordon, Anthony C; Gurusamy, Kurinchi S
2016-05-01
Septic shock is a life-threatening condition requiring vasopressor agents to support the circulatory system. Several agents exist with choice typically guided by the specific clinical scenario. We used a network meta-analysis approach to rate the comparative efficacy and safety of vasopressors for mortality and arrhythmia incidence in septic shock patients. We performed a comprehensive electronic database search including Medline, Embase, Science Citation Index Expanded and the Cochrane database. Randomised trials investigating vasopressor agents in septic shock patients and specifically assessing 28-day mortality or arrhythmia incidence were included. A Bayesian network meta-analysis was performed using Markov chain Monte Carlo methods. Thirteen trials of low to moderate risk of bias in which 3146 patients were randomised were included. There was no pairwise evidence to suggest one agent was superior over another for mortality. In the network meta-analysis, vasopressin was significantly superior to dopamine (OR 0.68 (95% CI 0.5 to 0.94)) for mortality. For arrhythmia incidence, standard pairwise meta-analyses confirmed that dopamine led to a higher incidence of arrhythmias than norepinephrine (OR 2.69 (95% CI 2.08 to 3.47)). In the network meta-analysis, there was no evidence of superiority of one agent over another. In this network meta-analysis, vasopressin was superior to dopamine for 28-day mortality in septic shock. Existing pairwise information supports the use of norepinephrine over dopamine. Our findings suggest that dopamine should be avoided in patients with septic shock and that other vasopressor agents should continue to be based on existing guidelines and clinical judgement of the specific presentation of the patient.
Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks
NASA Astrophysics Data System (ADS)
Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa
In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.
Towards effective payoffs in the prisoner’s dilemma game on scale-free networks
NASA Astrophysics Data System (ADS)
Szolnoki, Attila; Perc, Matjaž; Danku, Zsuzsa
2008-03-01
We study the transition towards effective payoffs in the prisoner's dilemma game on scale-free networks by introducing a normalization parameter guiding the system from accumulated payoffs to payoffs normalized with the connectivity of each agent. We show that during this transition the heterogeneity-based ability of scale-free networks to facilitate cooperative behavior deteriorates continuously, eventually collapsing with the results obtained on regular graphs. The strategy donations and adaptation probabilities of agents with different connectivities are studied. Results reveal that strategies generally spread from agents with larger towards agents with smaller degree. However, this strategy adoption flow reverses sharply in the fully normalized payoff limit. Surprisingly, cooperators occupy the hubs even if the averaged cooperation level due to partly normalized payoffs is moderate.
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.
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.
Song, Qiang; Liu, Fang; Wen, Guanghui; Cao, Jinde; Yang, Xinsong
2017-04-24
This paper considers the position-based consensus in a network of agents with double-integrator dynamics and directed topology. Two types of distributed observer algorithms are proposed to solve the consensus problem by utilizing continuous and intermittent position measurements, respectively, where each observer does not interact with any other observers. For the case of continuous communication between network agents, some convergence conditions are derived for reaching consensus in the network with a single constant delay or multiple time-varying delays on the basis of the eigenvalue analysis and the descriptor method. When the network agents can only obtain intermittent position data from local neighbors at discrete time instants, the consensus in the network without time delay or with nonuniform delays is investigated by using the Wirtinger's inequality and the delayed-input approach. Numerical examples are given to illustrate the theoretical analysis.
Collective decision dynamics in the presence of external drivers
NASA Astrophysics Data System (ADS)
Bassett, Danielle S.; Alderson, David L.; Carlson, Jean M.
2012-09-01
We develop a sequence of models describing information transmission and decision dynamics for a network of individual agents subject to multiple sources of influence. Our general framework is set in the context of an impending natural disaster, where individuals, represented by nodes on the network, must decide whether or not to evacuate. Sources of influence include a one-to-many externally driven global broadcast as well as pairwise interactions, across links in the network, in which agents transmit either continuous opinions or binary actions. We consider both uniform and variable threshold rules on the individual opinion as baseline models for decision making. Our results indicate that (1) social networks lead to clustering and cohesive action among individuals, (2) binary information introduces high temporal variability and stagnation, and (3) information transmission over the network can either facilitate or hinder action adoption, depending on the influence of the global broadcast relative to the social network. Our framework highlights the essential role of local interactions between agents in predicting collective behavior of the population as a whole.
Prediction of competitive diffusion on complex networks
NASA Astrophysics Data System (ADS)
Zhao, Jiuhua; Liu, Qipeng; Wang, Lin; Wang, Xiaofan
2018-10-01
In this paper, we study the prediction problem of diffusion process on complex networks in competitive circumstances. With this problem solved, the competitors could timely intervene the diffusion process if needed such that an expected outcome might be obtained. We consider a model with two groups of competitors spreading opposite opinions on a network. A prediction method based on the mutual influences among the agents is proposed, called Influence Matrix (IM for short), and simulations on real-world networks show that the proposed IM method has quite high accuracy on predicting both the preference of any normal agent and the final competition result. For comparison purpose, classic centrality measures are also used to predict the competition result. It is shown that PageRank, Degree, Katz Centrality, and the IM method are suitable for predicting the competition result. More precisely, in undirected networks, the IM method performs better than these centrality measures when the competing group contains more than one agent; in directed networks, the IM method performs only second to PageRank.
A network model of knowledge accumulation through diffusion and upgrade
NASA Astrophysics Data System (ADS)
Zhuang, Enyu; Chen, Guanrong; Feng, Gang
2011-07-01
In this paper, we introduce a model to describe knowledge accumulation through knowledge diffusion and knowledge upgrade in a multi-agent network. Here, knowledge diffusion refers to the distribution of existing knowledge in the network, while knowledge upgrade means the discovery of new knowledge. It is found that the population of the network and the number of each agent’s neighbors affect the speed of knowledge accumulation. Four different policies for updating the neighboring agents are thus proposed, and their influence on the speed of knowledge accumulation and the topology evolution of the network are also studied.
Gefragte Talente. Türkeistämmige Hochqualifizierte in deutschen Unternehmen in der Türkei
NASA Astrophysics Data System (ADS)
Müller, Philip
2017-04-01
The recruitment of qualified employees is a key component for the economic success of subsidiary companies in foreign countries. This article underlines that persons with migration backgrounds and German university degrees are not only important resources for firms in Germany, but also for German subsidiaries located abroad. Using the example of academics of Turkish origin, this empirical case underlines that German firms can profit from the remigration of skilled migrants to their home countries. In German subsidiaries based in Turkey skilled migrants of Turkish origin are often deployed in positions that have close interfaces to German locations due to their expertise and intercultural competences. Their high physical and virtual mobility in addition to their transnational networks strengthen the inter-location cooperation.
Phase Transition in Opinion Diffusion in Social Networks
2012-05-01
the opinions of social agents diffuse in a network under a so-called hard-interaction model, in which the agents inter- act more strongly with...gent behavior. Index Terms— opinion diffusion , opinion dynamics, social net- works, phase transition, herding. 1. INTRODUCTION The study of the
Memory Transmission in Small Groups and Large Networks: An Agent-Based Model.
Luhmann, Christian C; Rajaram, Suparna
2015-12-01
The spread of social influence in large social networks has long been an interest of social scientists. In the domain of memory, collaborative memory experiments have illuminated cognitive mechanisms that allow information to be transmitted between interacting individuals, but these experiments have focused on small-scale social contexts. In the current study, we took a computational approach, circumventing the practical constraints of laboratory paradigms and providing novel results at scales unreachable by laboratory methodologies. Our model embodied theoretical knowledge derived from small-group experiments and replicated foundational results regarding collaborative inhibition and memory convergence in small groups. Ultimately, we investigated large-scale, realistic social networks and found that agents are influenced by the agents with which they interact, but we also found that agents are influenced by nonneighbors (i.e., the neighbors of their neighbors). The similarity between these results and the reports of behavioral transmission in large networks offers a major theoretical insight by linking behavioral transmission to the spread of information. © The Author(s) 2015.
Collective navigation of complex networks: Participatory greedy routing.
Kleineberg, Kaj-Kolja; Helbing, Dirk
2017-06-06
Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the navigation. This organizational principle can be exploited to favor the emergence of global navigability in the system.
Bonhomme, Vincent; Boveroux, Pierre; Hans, Pol; Brichant, Jean François; Vanhaudenhuyse, Audrey; Boly, Melanie; Laureys, Steven
2011-10-01
To describe recent studies exploring brain function under the influence of hypnotic anesthetic agents, and their implications on the understanding of consciousness physiology and anesthesia-induced alteration of consciousness. Cerebral cortex is the primary target of the hypnotic effect of anesthetic agents, and higher-order association areas are more sensitive to this effect than lower-order processing regions. Increasing concentration of anesthetic agents progressively attenuates connectivity in the consciousness networks, while connectivity in lower-order sensory and motor networks is preserved. Alteration of thalamic sub-cortical regulation could compromise the cortical integration of information despite preserved thalamic activation by external stimuli. At concentrations producing unresponsiveness, the activity of consciousness networks becomes anticorrelated with thalamic activity, while connectivity in lower-order sensory networks persists, although with cross-modal interaction alterations. Accumulating evidence suggests that hypnotic anesthetic agents disrupt large-scale cerebral connectivity. This would result in an inability of the brain to generate and integrate information, while external sensory information is still processed at a lower order of complexity.
Tackling Information Asymmetry in Networks: A New Entropy-Based Ranking Index
NASA Astrophysics Data System (ADS)
Barucca, Paolo; Caldarelli, Guido; Squartini, Tiziano
2018-06-01
Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel index—InfoRank—intended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.
Structural stability of interaction networks against negative external fields
NASA Astrophysics Data System (ADS)
Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.
2018-04-01
We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.
Mechanisms and dynamics of cooperation and competition emergence in complex networked systems
NASA Astrophysics Data System (ADS)
Gianetto, David A.
Cooperative behavior is a pervasive phenomenon in human interactions and yet how it can evolve and become established, through the selfish process of natural selection, is an enduring puzzle. These behaviors emerge when agents interact in a structured manner; even so, the key structural factors that affect cooperation are not well understood. Moreover, the literature often considers cooperation a single attribute of primitive agents who do not react to environmental changes but real-world actors are more perceptive. The present work moves beyond these assumptions by evolving more realistic game participants, with memories of the past, on complex networks. Agents play repeated games with a three-part Markovian strategy that allows us to separate the cooperation phenomenon into trust, reciprocity, and forgiveness characteristics. Our results show that networks matter most when agents gain the most by acting in a selfish manner, irrespective of how much they may lose by cooperating; since the context provided by neighborhoods inhibits greedy impulses that agents otherwise succumb to in isolation. Network modularity is the most important driver of cooperation emergence in these high-stakes games. However, modularity fails to tell the complete story. Modular scale-free graphs impede cooperation when close coordination is required, partially due to the acyclic nature of scale-free network models. To achieve the highest cooperation in diverse social conditions, both high modularity, low connectivity within modules, and a rich network of long cycles become important. With these findings in hand, we study the influence of networks on coordination and competition within the federal health care insurance exchange. In this applied study, we show that systemic health care coordination is encouraged by the emergent insurance network. The network helps underpin the viability of the exchange and provides an environment of stronger competition once a critical-mass of insurers have entered the market.
An economic model of friendship and enmity for measuring social balance in networks
NASA Astrophysics Data System (ADS)
Lee, Kyu-Min; Shin, Euncheol; You, Seungil
2017-12-01
We propose a dynamic economic model of networks where agents can be friends or enemies with one another. This is a decentralized relationship model in that agents decide whether to change their relationships so as to minimize their imbalanced triads. In this model, there is a single parameter, which we call social temperature, that captures the degree to which agents care about social balance in their relationships. We show that the global structure of relationship configuration converges to a unique stationary distribution. Using this stationary distribution, we characterize the maximum likelihood estimator of the social temperature parameter. Since the estimator is computationally challenging to calculate from real social network datasets, we provide a simple simulation algorithm and verify its performance with real social network datasets.
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.
NPS Collaborative Technology Testbed for ONR CKM Program
2005-01-11
or have access to the MIT E-Wall hosted by the TOC. The combination of E-Wall and agents lend themselves to the dynamic gathering and display of...display, intuitive icons or menus that is easy to activate and customize , and automatically seeks and connects to other like services/networks/agents...integration creates network- centric memory mechanism for developing shared understanding of SA events Data Base Integration of Sensor-DM Agents and
NASA Astrophysics Data System (ADS)
Ausloos, Marcel
2015-06-01
Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.
ERIC Educational Resources Information Center
De Stasio, Elizabeth A.; Ansfield, Matthew; Cohen, Paul; Spurgin, Timothy
2009-01-01
Most American students enter college at a time when they are still forging their identities and seeking a place in the world. Yet many or most of today's students are increasingly dependent on their parents and stay more firmly connected to previous support networks via the "electronic tether" than did their predecessors. In this article, the…
Collegiate Cyber Defense Competition Effort
2018-03-01
Energy – an electrical utility company. • 2016 : ODIN Security – a small aerospace and defense contracting firm Approved for Public Release...to secure supervisory control and data acquisition (SCADA) networks. Approved for Public Release; Distribution Unlimited 7 During the 2016 NCCDC...COLLEGIATE CYBER DEFENSE COMPETITION EFFORT UNIVERSITY OF TEXAS AT SAN ANTONIO MARCH 2018 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE
Benefits of Including a Capstone Simulation Course in Community College Business Curricula.
ERIC Educational Resources Information Center
Black, William L.
This article makes an argument for including a capstone, or end-of-term, business simulation course in community college business curricula. The International Business Practice Firm (IBPF), a worldwide virtual business network, is proposed as a foundation for such a course. The author argues that, in general, graduates of college business programs…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-05-12
..., Including On-Site Leased Workers of Adecco USA, Inc., Aerotek, Inc., the Bartech Group, Back Diamonds Networks, Entegee, Inc., DBA Midstates Technical, Manpower, Inc., Robert Half International, Summit... part that was used by a firm that employed a worker group currently eligible to apply for TAA. The...
ERIC Educational Resources Information Center
Balogun, Shereef Adewale
2013-01-01
Information technology (IT) outsourcing is a practical way to transfer information technology by industries of different firms. The problem occurs when companies outsource services to domestic and international data centers as network security issues arise. This leads to competition between companies causing the size of the company to become more…
ERIC Educational Resources Information Center
Indiana Career and Postsecondary Advancement Center, Bloomington.
This packet documents suggestions for conducting a job search, writing a resume, and interviewing. Suggestions for a job search include the following: knowing one's skills, knowing what one is looking for, and knowing where to look for jobs, including newspaper advertisements, employment centers, employment firms, networking, and blind attempts.…
Zhang, Jun; Shoham, David A.; Tesdahl, Eric
2015-01-01
Objectives. We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children’s physical activity. We tested 3 intervention strategies. Results. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children’s physical activity. PMID:25689202
Wu, Chunxue; Wu, Wenliang; Wan, Caihua
2017-01-01
Sensors are increasingly used in mobile environments with wireless network connections. Multiple sensor types measure distinct aspects of the same event. Their measurements are then combined to produce integrated, reliable results. As the number of sensors in networks increases, low energy requirements and changing network connections complicate event detection and measurement. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the data fusion at the migration node. Agents use the fusion results to decide if it should return the fusion results to the processing center or continue to collect more data. In the second phase. The feasibility of data fusion at the node level is confirmed by an experimental design where fused data from color sensors show near-identical results to actual physical temperatures. These results are potentially important for new large-scale sensor network applications. PMID:29099793
Smith, Timothy M; Goodkind, Andrew L; Kim, Taegon; Pelton, Rylie E O; Suh, Kyo; Schmitt, Jennifer
2017-09-19
Corn production, and its associated inputs, is a relatively large source of greenhouse gas emissions and uses significant amounts of water and land, thus contributing to climate change, fossil fuel depletion, local air pollutants, and local water scarcity. As large consumers of this corn, corporations in the ethanol and animal protein industries are increasingly assessing and reporting sustainability impacts across their supply chains to identify, prioritize, and communicate sustainability risks and opportunities material to their operations. In doing so, many have discovered that the direct impacts of their owned operations are dwarfed by those upstream in the supply chain, requiring transparency and knowledge about environmental impacts along the supply chains. Life cycle assessments (LCAs) have been used to identify hotspots of environmental impacts at national levels, yet these provide little subnational information necessary for guiding firms' specific supply networks. In this paper, our Food System Supply-Chain Sustainability (FoodS 3 ) model connects spatial, firm-specific demand of corn purchasers with upstream corn production in the United States through a cost minimization transport model. This provides a means to link county-level corn production in the United States to firm-specific demand locations associated with downstream processing facilities. Our model substantially improves current LCA assessment efforts that are confined to broad national or state level impacts. In drilling down to subnational levels of environmental impacts that occur over heterogeneous areas and aggregating these landscape impacts by specific supply networks, targeted opportunities for improvements to the sustainability performance of supply chains are identified.
Supply network configuration—A benchmarking problem
NASA Astrophysics Data System (ADS)
Brandenburg, Marcus
2018-03-01
Managing supply networks is a highly relevant task that strongly influences the competitiveness of firms from various industries. Designing supply networks is a strategic process that considerably affects the structure of the whole network. In contrast, supply networks for new products are configured without major adaptations of the existing structure, but the network has to be configured before the new product is actually launched in the marketplace. Due to dynamics and uncertainties, the resulting planning problem is highly complex. However, formal models and solution approaches that support supply network configuration decisions for new products are scant. The paper at hand aims at stimulating related model-based research. To formulate mathematical models and solution procedures, a benchmarking problem is introduced which is derived from a case study of a cosmetics manufacturer. Tasks, objectives, and constraints of the problem are described in great detail and numerical values and ranges of all problem parameters are given. In addition, several directions for future research are suggested.
The New Agent: A Qualitative Study to Strategically Adapt New Agent Professional Development
ERIC Educational Resources Information Center
Baker, Lauri M.; Hadley, Gregg
2014-01-01
The qualitative study reported here assessed the needs of agents related to new agent professional development to improve the current model. Agents who participated in new agent professional development within the last 5 years were selected to participate in focus groups to determine concerns and continued needs. Agents enjoyed networking and…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mahault, Benoit Alexandre; Saxena, Avadh Behari; Nisoli, Cristiano
We introduce a minimal agent-based model to qualitatively conceptualize the allocation of limited wealth among more abundant opportunities. We study the interplay of power, satisfaction and frustration in the problem of wealth distribution, concentration, and inequality. This framework allows us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from, or lose wealth to, anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity, onlymore » minimally ameliorated by disorder in a non-optimized society. The picture is however dramatically modified when hard constraints are imposed over agents, and they are forced to share wealth with neighbors on a network. We discuss the case of random networks and scale free networks. We then propose an out of equilibrium dynamics of the networks, based on a competition of power and frustration in the decision-making of agents that leads to network evolution. We show that the ratio of power and frustration controls different dynamical regimes separated by kinetic transition and characterized by drastically different values of the indices of equality.« less
Automation of multi-agent control for complex dynamic systems in heterogeneous computational network
NASA Astrophysics Data System (ADS)
Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan
2017-01-01
The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.
Directed Random Markets: Connectivity Determines Money
NASA Astrophysics Data System (ADS)
Martínez-Martínez, Ismael; López-Ruiz, Ricardo
2013-12-01
Boltzmann-Gibbs (BG) distribution arises as the statistical equilibrium probability distribution of money among the agents of a closed economic system where random and undirected exchanges are allowed. When considering a model with uniform savings in the exchanges, the final distribution is close to the gamma family. In this paper, we implement these exchange rules on networks and we find that these stationary probability distributions are robust and they are not affected by the topology of the underlying network. We introduce a new family of interactions: random but directed ones. In this case, it is found the topology to be determinant and the mean money per economic agent is related to the degree of the node representing the agent in the network. The relation between the mean money per economic agent and its degree is shown to be linear.
Partner switching promotes cooperation among myopic agents on a geographical plane
NASA Astrophysics Data System (ADS)
Li, Yixiao; Min, Yong; Zhu, Xiaodong; Cao, Jie
2013-02-01
We study the coupling dynamics between the evolution of cooperation and the evolution of partnership network on a geographical plane. While agents play networked prisoner’s dilemma games, they can dynamically adjust their partnerships based on local information about reputation. We incorporate geographical features into the process of the agent’s partner switching and investigate the corresponding effects. At each time step of the coevolution, a random agent can either update his strategy by imitation or adjust his partnership by switching from the lowest reputation partner to the highest reputation one among his neighbors. We differentiate two types of neighbors: geographical neighbors (i.e., the set of agents who are close to the focal agent in terms of geographical distance) and connectivity neighbors (i.e., the set of agents who are close to the focal agent in the partnership network in terms of geodesic distance). We find that switching to either geographical neighbors or connectivity neighbors enhances cooperation greatly in a wide parameter range. Cooperation can be favored in a much stricter condition when agents switch to connectivity neighbors more frequently. However, an increasing tendency of reconnecting to geographical neighbors shortens the geographical distance between a pair of partners on average. When agents consider the cost of geographical distance in adjusting the partnership, they are prone to reconnect to geographical neighbors.
Collective motion patterns of swarms with delay coupling: Theory and experiment.
Szwaykowska, Klementyna; Schwartz, Ira B; Mier-Y-Teran Romero, Luis; Heckman, Christoffer R; Mox, Dan; Hsieh, M Ani
2016-03-01
The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.
Collective motion patterns of swarms with delay coupling: Theory and experiment
NASA Astrophysics Data System (ADS)
Szwaykowska, Klementyna; Schwartz, Ira B.; Mier-y-Teran Romero, Luis; Heckman, Christoffer R.; Mox, Dan; Hsieh, M. Ani
2016-03-01
The formation of coherent patterns in swarms of interacting self-propelled autonomous agents is a subject of great interest in a wide range of application areas, ranging from engineering and physics to biology. In this paper, we model and experimentally realize a mixed-reality large-scale swarm of delay-coupled agents. The coupling term is modeled as a delayed communication relay of position. Our analyses, assuming agents communicating over an Erdös-Renyi network, demonstrate the existence of stable coherent patterns that can be achieved only with delay coupling and that are robust to decreasing network connectivity and heterogeneity in agent dynamics. We also show how the bifurcation structure for emergence of different patterns changes with heterogeneity in agent acceleration capabilities and limited connectivity in the network as a function of coupling strength and delay. Our results are verified through simulation as well as preliminary experimental results of delay-induced pattern formation in a mixed-reality swarm.
Basic Lessons in ORA and AutoMap 2011
2011-06-13
A small legend also appears. Below is a screen capture showing the visualization of the agent x event graph from the Stargate Summit Meta-Network...4 The visualization displays the connections between all items in the Stargate Summit Meta-Network. The red circles represent the agents, the...It takes the examples I used for the Stargate dataset. 5 lessons - 201-207 A step by step run through of creating the Meta-Network from
Complex Dynamics in Information Sharing Networks
NASA Astrophysics Data System (ADS)
Cronin, Bruce
This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.
Dynamic Network Security Control Using Software Defined Networking
2016-03-24
Most importantly I thank my family for understanding, loving , and thriving in the hectic world of military spouse and children. Michael C. Todd v...RBAC poses access to objects as a user to member-of group relationship . This construct results in a set of rules to govern access to objects based...API. Agent Agent.py Event.py Message.py ModSysStatus.py Event Message ModSysStatus Event - Message - ModSysStatus Relationship Figure 12. Agent Design
Fault Tolerant Airborne Sensor Networks for Air Operations
2008-02-01
lives affected by undetected targets. The network is said to have expired when there is no longer a single surviving sensor-pair. Tasking process...tasking a finite number of cooperative agents to randomly emerging targets for their removal. Faults occur when some agents engaged in a mission are...expired. Agents are subject to threat at a level determined by the number of targets present. On the other hand, the rate at which a target is removed
Large-Scale Cooperative Task Distribution on Peer-to-Peer Networks
2012-01-01
SUBTITLE Large-scale cooperative task distribution on peer-to-peer networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...of agents, and each agent attempts to form a coalition with its most profitable partner. The second algorithm builds upon the Shapley for- mula [37...ters at the second layer. These Category Layer clusters each represent a single resource, and agents join one or more clusters based on their
NASA Astrophysics Data System (ADS)
Zimmermann, Martín G.; Eguíluz, Víctor M.
2005-11-01
Cooperative behavior among a group of agents is studied assuming adaptive interactions. Each agent plays a Prisoner’s Dilemma game with its local neighbors, collects an aggregate payoff, and imitates the strategy of its best neighbor. Agents may punish or reward their neighbors by removing or sustaining the interactions, according to their satisfaction level and strategy played. An agent may dismiss an interaction, and the corresponding neighbor is replaced by another randomly chosen agent, introducing diversity and evolution to the network structure. We perform an extensive numerical and analytical study, extending results in M. G. Zimmermann, V. M. Eguíluz, and M. San Miguel, Phys. Rev. E 69, 065102(R) (2004). We show that the system typically reaches either a full-defective state or a highly cooperative steady state. The latter equilibrium solution is composed mostly by cooperative agents, with a minor population of defectors that exploit the cooperators. It is shown how the network adaptation dynamics favors the emergence of cooperators with the highest payoff. These “leaders” are shown to sustain the global cooperative steady state. Also we find that the average payoff of defectors is larger than the average payoff of cooperators. Whenever “leaders” are perturbed (e.g., by addition of noise), an unstable situation arises and global cascades with oscillations between the nearly full defection network and the fully cooperative outcome are observed.
NASA Astrophysics Data System (ADS)
Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen
2014-05-01
When investigating the causes and consequences of global change, the collective behavior of human beings is considered as having a considerable impact on natural systems. In our work, we propose a conceptual coevolutionary model simulating the dynamics of local renewable resources in interaction with simplistic societal agents exploiting those resources. The society is represented by a social network on which social traits may be transmitted between agents. These traits themselves induce a certain rate of exploitation of the resource, leading either to its depletion or sustainable existence. Traits are exchanged probabilistically according to their instantaneous individual payoff, and hence this process depends on the status of the natural resource. At the same time agents may adaptively restructure their set of acquaintances. Connections with agents having a different trait may be broken while new connections with agents of the same trait are established. We investigate which choices of social parameters, like the frequency of social interaction, rationality and rate of social network adaptation, cause the system to end in a sustainable state and, hence, what can be done to avoid a collapse of the entire system. The importance and influence of the social network structure is analyzed by the variation of link-densities in the underlying network topology and shows significant influence on the expected outcome of the model. For a static network with no adaptation we find a robust phase transition between the two different regimes, sustainable and non-sustainable, which co-exist in parameter space. High connectivity within the social network, e.g., high link-densities, in combination with a fast rate of social learning lead to a likely collapse of the entire co-evolutionary system, whereas slow learning and small network connectivity very likely result in the sustainable existence of the natural resources. Collapse may be avoided by an intelligent rewiring, e.g. adaptation, of the social network that may also lead to the isolation of misbehaving parts of the society. Our results may suggest that with the current trend to faster imitation and ever increasing global network connectivity, societies are becoming more vulnerable to environmental collapse if they remain myopic at the same time.
Synchronization control in multiplex networks of nonlinear multi-agent systems
NASA Astrophysics Data System (ADS)
He, Wangli; Xu, Zhiwei; Du, Wenli; Chen, Guanrong; Kubota, Naoyuki; Qian, Feng
2017-12-01
This paper is concerned with synchronization control of a multiplex network, in which two different kinds of relationships among agents coexist. Hybrid coupling, including continuous linear coupling and impulsive coupling, is proposed to model the coexisting distinguishable interactions. First, by adding impulsive controllers on a small portion of agents, local synchronization is analyzed by linearizing the error system at the desired trajectory. Then, global synchronization is studied based on the Lyapunov stability theory, where a time-varying coupling strength is involved. To further deal with the time-varying coupling strength, an adaptive updating law is introduced and a corresponding sufficient condition is obtained to ensure synchronization of the multiplex network towards the desired trajectory. Networks of Chua's circuits and other chaotic systems with double layers of interactions are simulated to verify the proposed method.
Interaction and Communication of Agents in Networks and Language Complexity Estimates
NASA Technical Reports Server (NTRS)
Smid, Jan; Obitko, Marek; Fisher, David; Truszkowski, Walt
2004-01-01
Knowledge acquisition and sharing are arguably the most critical activities of communicating agents. We report about our on-going project featuring knowledge acquisition and sharing among communicating agents embedded in a network. The applications we target range from hardware robots to virtual entities such as internet agents. Agent experiments can be simulated using a convenient simulation language. We analyzed the complexity of communicating agent simulations using Java and Easel. Scenarios we have studied are listed below. The communication among agents can range from declarative queries to sub-natural language queries. 1) A set of agents monitoring an object are asked to build activity profiles based on exchanging elementary observations; 2) A set of car drivers form a line, where every car is following its predecessor. An unsafe distance cm create a strong wave in the line. Individual agents are asked to incorporate and apply directions how to avoid the wave. 3) A set of micro-vehicles form a grid and are asked to propagate information and concepts to a central server.
How star women build portable skills.
Groysberg, Boris
2008-02-01
In May 2004, with the war for talent in high gear, Groysberg and colleagues from Harvard Business School wrote in these pages about the risks of hiring star performers away from competitors. After studying the fortunes of more than 1,000 star stock analysts, they found that when a star switched companies, not only did his performance plunge, so did the effectiveness of the group he joined and the market value of his new company. But further analysis of the data reveals that it's not that simple. In fact, one group of analysts reliably maintained star rankings even after changing employers: women. Unlike their male counterparts, female stars who switched firms performed just as well, in the aggregate, as those who stayed put. The 189 star women in the sample (18% of the star analysts studied) achieved a higher rank after switching firms than the men did. Why the discrepancy? First, says the author, the best female analysts appear to have built their franchises on portable, external relationships with clients and the companies they covered, rather than on relationships rooted within their firms. By contrast, male analysts built up greater firm- and team-specific human capital by investing more in the internal networks and unique capabilities and resources of their own companies. Second, women took greater care when assessing a prospective new employer. In this article, Groysberg explores the reasons behind the star women's portable performance.
Vector-based navigation using grid-like representations in artificial agents.
Banino, Andrea; Barry, Caswell; Uria, Benigno; Blundell, Charles; Lillicrap, Timothy; Mirowski, Piotr; Pritzel, Alexander; Chadwick, Martin J; Degris, Thomas; Modayil, Joseph; Wayne, Greg; Soyer, Hubert; Viola, Fabio; Zhang, Brian; Goroshin, Ross; Rabinowitz, Neil; Pascanu, Razvan; Beattie, Charlie; Petersen, Stig; Sadik, Amir; Gaffney, Stephen; King, Helen; Kavukcuoglu, Koray; Hassabis, Demis; Hadsell, Raia; Kumaran, Dharshan
2018-05-01
Deep neural networks have achieved impressive successes in fields ranging from object recognition to complex games such as Go 1,2 . Navigation, however, remains a substantial challenge for artificial agents, with deep neural networks trained by reinforcement learning 3-5 failing to rival the proficiency of mammalian spatial behaviour, which is underpinned by grid cells in the entorhinal cortex 6 . Grid cells are thought to provide a multi-scale periodic representation that functions as a metric for coding space 7,8 and is critical for integrating self-motion (path integration) 6,7,9 and planning direct trajectories to goals (vector-based navigation) 7,10,11 . Here we set out to leverage the computational functions of grid cells to develop a deep reinforcement learning agent with mammal-like navigational abilities. We first trained a recurrent network to perform path integration, leading to the emergence of representations resembling grid cells, as well as other entorhinal cell types 12 . We then showed that this representation provided an effective basis for an agent to locate goals in challenging, unfamiliar, and changeable environments-optimizing the primary objective of navigation through deep reinforcement learning. The performance of agents endowed with grid-like representations surpassed that of an expert human and comparison agents, with the metric quantities necessary for vector-based navigation derived from grid-like units within the network. Furthermore, grid-like representations enabled agents to conduct shortcut behaviours reminiscent of those performed by mammals. Our findings show that emergent grid-like representations furnish agents with a Euclidean spatial metric and associated vector operations, providing a foundation for proficient navigation. As such, our results support neuroscientific theories that see grid cells as critical for vector-based navigation 7,10,11 , demonstrating that the latter can be combined with path-based strategies to support navigation in challenging environments.
Industrial entrepreneurial network: Structural and functional analysis
NASA Astrophysics Data System (ADS)
Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.
2016-12-01
Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.
The prisoner’s dilemma on co-evolving networks under perfect rationality
NASA Astrophysics Data System (ADS)
Biely, Christoly; Dragosits, Klaus; Thurner, Stefan
2007-04-01
We consider the prisoner’s dilemma being played repeatedly on a dynamic network, where agents may choose their actions as well as their co-players. This leads to co-evolution of network structure and strategy patterns of the players. Individual decisions are made fully rationally and are based on local information only. They are made such that links to defecting agents are resolved and that cooperating agents build up new links. The exact form of the updating scheme is motivated by profit maximization and not by imitation. If players update their decisions in a synchronized way the system exhibits oscillatory dynamics: Periods of growing cooperation (and total linkage) alternate with periods of increasing defection. The cyclical behavior is reduced and the system stabilizes at significant total cooperation levels when players are less synchronized. In this regime we find emergent network structures resembling ‘complex’ and hierarchical topology. The exponent of the power-law degree distribution ( γ∼8.6) perfectly matches empirical results for human communication networks.
Agnew, Douglas W; DiMucci, Ida M; Arroyave, Alejandra; Gembicky, Milan; Moore, Curtis E; MacMillan, Samantha N; Rheingold, Arnold L; Lancaster, Kyle M; Figueroa, Joshua S
2017-12-06
A permanently porous, three-dimensional metal-organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2 ] 2 , and the d 10 Ni(0) precursor Ni(COD) 2 , produces a porous metal-organic material featuring tetrahedral [Ni(CNAr Mes2 ) 4 ] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2 -adsorption profile.
Agnew, Douglas W.; DiMucci, Ida M.; Arroyave, Alejandra; ...
2017-11-13
A permanently porous, three-dimensional metal–organic material formed from zero-valent metal nodes is presented. Combination of ditopic m-terphenyl diisocyanide, [CNAr Mes2] 2, and the d 10 Ni(0) precursor Ni(COD) 2, produces a porous metal–organic material featuring tetrahedral [Ni(CNAr Mes2) 4] n structural sites. X-ray absorption spectroscopy provides firm evidence for the presence of Ni(0) centers, whereas gas-sorption and thermogravimetric analysis reveal the characteristics of a robust network with a microdomain N 2-adsorption profile.
NASA Astrophysics Data System (ADS)
Patkin, M. L.; Rogachev, G. N.
2018-02-01
A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.
Dynamics of Research Team Formation in Complex Networks
NASA Astrophysics Data System (ADS)
Sun, Caihong; Wan, Yuzi; Chen, Yu
Most organizations encourage the formation of teams to accomplish complicated tasks, and vice verse, effective teams could bring lots benefits and profits for organizations. Network structure plays an important role in forming teams. In this paper, we specifically study the dynamics of team formation in large research communities in which knowledge of individuals plays an important role on team performance and individual utility. An agent-based model is proposed, in which heterogeneous agents from research communities are described and empirically tested. Each agent has a knowledge endowment and a preference for both income and leisure. Agents provide a variable input (‘effort’) and their knowledge endowments to production. They could learn from others in their team and those who are not in their team but have private connections in community to adjust their own knowledge endowment. They are allowed to join other teams or work alone when it is welfare maximizing to do so. Various simulation experiments are conducted to examine the impacts of network topology, knowledge diffusion among community network, and team output sharing mechanisms on the dynamics of team formation.
Remote Data Retrieval for Bioinformatics Applications: An Agent Migration Approach
Gao, Lei; Dai, Hua; Zhang, Tong-Liang; Chou, Kuo-Chen
2011-01-01
Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach. PMID:21701677
Intelligent sensor and controller framework for the power grid
Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim
2015-07-28
Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.
Intelligent sensor and controller framework for the power grid
DOE Office of Scientific and Technical Information (OSTI.GOV)
Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen
Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with themore » software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.« less
Agent-based approach for generation of a money-centered star network
NASA Astrophysics Data System (ADS)
Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook
2008-09-01
The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.
A Review of Theoretical Frameworks for Supply Chain Integration
NASA Astrophysics Data System (ADS)
Thoo, AC; Tan, LC; Sulaiman, Z.; Zakuan, N.
2017-06-01
In a world of fierce competition and business driven by speed to market, good quality and low costs, this environment requires firms to have a source of competitive advantage that is inimitable and non-substitutable. For a supply chain integration (SCI) strategy to achieve sustainable competitive advantage it must be non-substitutable, inimitable, path-dependent and developed over time. Also, an integrated supply chain framework is needed to tie the whole network together in order to reduce perennial supply chain challenges such as functional silos, poor transparency of knowledge and information and the inadequate formation of appropriate customer and supplier relationships. Therefore, this paper aims to evaluate the competitive impact of a SCI strategy on firm performance using the theory of Resource-based View (RBV) and relational view.
Connection adaption for control of networked mobile chaotic agents.
Zhou, Jie; Zou, Yong; Guan, Shuguang; Liu, Zonghua; Xiao, Gaoxi; Boccaletti, S
2017-11-22
In this paper, we propose a strategy for the control of mobile chaotic oscillators by adaptively rewiring connections between nearby agents with local information. In contrast to the dominant adaptive control schemes where coupling strength is adjusted continuously according to the states of the oscillators, our method does not request adaption of coupling strength. As the resulting interaction structure generated by this proposed strategy is strongly related to unidirectional chains, by investigating synchronization property of unidirectional chains, we reveal that there exists a certain coupling range in which the agents could be controlled regardless of the length of the chain. This feature enables the adaptive strategy to control the mobile oscillators regardless of their moving speed. Compared with existing adaptive control strategies for networked mobile agents, our proposed strategy is simpler for implementation where the resulting interaction networks are kept unweighted at all time.
NASA Astrophysics Data System (ADS)
Abdulghafoor, O. B.; Shaat, M. M. R.; Ismail, M.; Nordin, R.; Yuwono, T.; Alwahedy, O. N. A.
2017-05-01
In this paper, the problem of resource allocation in OFDM-based downlink cognitive radio (CR) networks has been proposed. The purpose of this research is to decrease the computational complexity of the resource allocation algorithm for downlink CR network while concerning the interference constraint of primary network. The objective has been secured by adopting pricing scheme to develop power allocation algorithm with the following concerns: (i) reducing the complexity of the proposed algorithm and (ii) providing firm power control to the interference introduced to primary users (PUs). The performance of the proposed algorithm is tested for OFDM- CRNs. The simulation results show that the performance of the proposed algorithm approached the performance of the optimal algorithm at a lower computational complexity, i.e., O(NlogN), which makes the proposed algorithm suitable for more practical applications.
Competitive STDP Learning of Overlapping Spatial Patterns.
Krunglevicius, Dalius
2015-08-01
Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.
Poyraz, Selcuk; Cerkez, Idris; Huang, Tung Shi; Liu, Zhen; Kang, Litao; Luo, Jujie; Zhang, Xinyu
2014-11-26
Through a facile and effective seeding polymerization reaction via a one-step redox/complexation process, which took place in aqueous medium at ambient temperature, silver nanoparticles (Ag NPs) embedded polyaniline nanofiber (PANI NF) networks were synthesized as antibacterial agents. During the reaction, not only NF morphology formation of the resulting conducting polymers (CPs) but also amplification of the aqueous silver nitrate (AgNO3) solutions' oxidative potentials were managed by vanadium pentoxide (V2O5) sol-gel nanofibers, which acted as well-known nanofibrous seeding agents and the auxiliary oxidative agent at the same time. The PANI/Ag nanocomposites were proven to exhibit excellent antibacterial property against both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus. Antibacterial property performance and average life span of the nanocomposite network were optimized through the homogeneous distribution/embedment of Ag NPs within one-dimensional (1-D) PANI NF matrix. The antibacterial efficacy tests and nanocomposite material characterization results further indicated that the sole components of PANI/Ag have a synergistic effect to each other in terms of antibacterial property. Thus, this well-known catalytic seeding approach via a one-step oxidative polymerization reaction can be considered as a general methodology and a substantial fabrication tool to synthesize Ag NP decorated nanofibrillar PANI networks as advanced antibacterial agents.
Enright, Jessica; Kao, Rowland R
2015-01-01
For diseases that infect humans or livestock, transmission dynamics are at least partially dependent on human activity and therefore human behaviour. However, the impact of human behaviour on disease transmission is relatively understudied, especially in the context of heterogeneous contact structures such as described by a social network. Here, we use a strategic game, coupled with a simple disease model, to investigate how strategic agent choices impact the spread of disease over a contact network. Using beliefs that are based on disease status and that build up over time, agents choose actions that stochastically determine disease spread on the network. An agent's disease status is therefore a function of both his own and his neighbours actions. The effect of disease on agents is modelled by a heterogeneous payoff structure. We find that the combination of network shape and distribution of payoffs has a non-trivial impact on disease prevalence, even if the mean payoff remains the same. An important scenario occurs when a small percentage (called noncooperators) have little incentive to avoid disease. For diseases that are easily acquired when taking a risk, then even when good behavior can lead to disease eradication, a small increase in the percentage of noncooperators (less than 5%) can yield a large (up to 25%) increase in prevalence.
ERIC Educational Resources Information Center
Phornprapha, Sarote
2015-01-01
With a vision that changes within the organisation could only happen through people, Chief Executive Officer Ms. Kaisri Nuengsigkapian led the creation of a successful workplace learning programme, People Passion within KPMG Thailand, which is part of a global network of professional firms providing audit, tax and advisory services. This article…
ERIC Educational Resources Information Center
Beach, Alta, Comp.
Designed to help business firms, corporations, researchers, and others identify libraries with major collections in the fields related to business that are accessible to the public, this brochure may also inform library staff of sources of information in the field for their own networking and for referrals of library users. An expanded and updated…
NASA Astrophysics Data System (ADS)
Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi
2017-07-01
Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.
ERIC Educational Resources Information Center
Rogers, Robert H.
In 1979, the National Aeronautics and Space Administration (NASA) and the Environmental Research Institute of Michigan (ERIM) initiated a program to investigate methods of making Landsat (satellite imagery) technology available to private sector firms through a network comprising NASA, a university or research institute, local community colleges,…
NASA Astrophysics Data System (ADS)
Helman, E. Udi
This dissertation conducts research into the large-scale simulation of oligopolistic competition in wholesale electricity markets. The dissertation has two parts. Part I is an examination of the structure and properties of several spatial, or network, equilibrium models of oligopolistic electricity markets formulated as mixed linear complementarity problems (LCP). Part II is a large-scale application of such models to the electricity system that encompasses most of the United States east of the Rocky Mountains, the Eastern Interconnection. Part I consists of Chapters 1 to 6. The models developed in this part continue research into mixed LCP models of oligopolistic electricity markets initiated by Hobbs [67] and subsequently developed by Metzler [87] and Metzler, Hobbs and Pang [88]. Hobbs' central contribution is a network market model with Cournot competition in generation and a price-taking spatial arbitrage firm that eliminates spatial price discrimination by the Cournot firms. In one variant, the solution to this model is shown to be equivalent to the "no arbitrage" condition in a "pool" market, in which a Regional Transmission Operator optimizes spot sales such that the congestion price between two locations is exactly equivalent to the difference in the energy prices at those locations (commonly known as locational marginal pricing). Extensions to this model are presented in Chapters 5 and 6. One of these is a market model with a profit-maximizing arbitrage firm. This model is structured as a mathematical program with equilibrium constraints (MPEC), but due to the linearity of its constraints, can be solved as a mixed LCP. Part II consists of Chapters 7 to 12. The core of these chapters is a large-scale simulation of the U.S. Eastern Interconnection applying one of the Cournot competition with arbitrage models. This is the first oligopolistic equilibrium market model to encompass the full Eastern Interconnection with a realistic network representation (using a DC load flow approximation). Chapter 9 shows the price results. In contrast to prior market power simulations of these markets, much greater variability in price-cost margins is found when using a realistic model of hourly conditions on such a large network. Chapter 10 shows that the conventional concentration indices (HHIs) are poorly correlated with PCMs. Finally, Chapter 11 proposes that the simulation models are applied to merger analysis and provides two large-scale merger examples. (Abstract shortened by UMI.)
NASA Technical Reports Server (NTRS)
1980-01-01
Visits to four utilities concerned with the use of DSG power sources on their distribution networks yielded useful impressions of present and future approaches to the integration of DSGs into electrical distribution network. Different approaches to future utility systems with DSG are beginning to take shape. The new DSG sources will be in decentralized locations with some measure of centralized control. The utilities have yet to establish firmly the communication and control means or their organization. For the present, the means for integrating the DSGs and their associated monitoring and control equipment into a unified system have not been decided.
Modeling infection transmission in primate networks to predict centrality-based risk.
Romano, Valéria; Duboscq, Julie; Sarabian, Cécile; Thomas, Elodie; Sueur, Cédric; MacIntosh, Andrew J J
2016-07-01
Social structure can theoretically regulate disease risk by mediating exposure to pathogens via social proximity and contact. Investigating the role of central individuals within a network may help predict infectious agent transmission as well as implement disease control strategies, but little is known about such dynamics in real primate networks. We combined social network analysis and a modeling approach to better understand transmission of a theoretical infectious agent in wild Japanese macaques, highly social animals which form extended but highly differentiated social networks. We collected focal data from adult females living on the islands of Koshima and Yakushima, Japan. Individual identities as well as grooming networks were included in a Markov graph-based simulation. In this model, the probability that an individual will transmit an infectious agent depends on the strength of its relationships with other group members. Similarly, its probability of being infected depends on its relationships with already infected group members. We correlated: (i) the percentage of subjects infected during a latency-constrained epidemic; (ii) the mean latency to complete transmission; (iii) the probability that an individual is infected first among all group members; and (iv) each individual's mean rank in the chain of transmission with different individual network centralities (eigenvector, strength, betweenness). Our results support the hypothesis that more central individuals transmit infections in a shorter amount of time and to more subjects but also become infected more quickly than less central individuals. However, we also observed that the spread of infectious agents on the Yakushima network did not always differ from expectations of spread on random networks. Generalizations about the importance of observed social networks in pathogen flow should thus be made with caution, since individual characteristics in some real world networks appear less relevant than they are in others in predicting disease spread. Am. J. Primatol. 78:767-779, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
An agent-based model of centralized institutions, social network technology, and revolution.
Makowsky, Michael D; Rubin, Jared
2013-01-01
This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.
Matching games with partial information
NASA Astrophysics Data System (ADS)
Laureti, Paolo; Zhang, Yi-Cheng
2003-06-01
We analyze different ways of pairing agents in a bipartite matching problem, with regard to its scaling properties and to the distribution of individual “satisfactions”. Then we explore the role of partial information and bounded rationality in a generalized Marriage Problem, comparing the benefits obtained by self-searching and by a matchmaker. Finally we propose a modified matching game intended to mimic the way consumers’ information makes firms to enhance the quality of their products in a competitive market.
Multiplex network analysis of employee performance and employee social relationships
NASA Astrophysics Data System (ADS)
Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene
2018-01-01
In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.
NASA Astrophysics Data System (ADS)
Soriano-Hernández, P.; del Castillo-Mussot, M.; Campirán-Chávez, I.; Montemayor-Aldrete, J. A.
2017-04-01
Forbes Magazine published its list of leading or strongest publicly-traded two thousand companies in the world (G-2000) based on four independent metrics: sales or revenues, profits, assets and market value. Every one of these wealth metrics yields particular information on the corporate size or wealth size of each firm. The G-2000 cumulative probability wealth distribution per employee (per capita) for all four metrics exhibits a two-class structure: quasi-exponential in the lower part, and a Pareto power-law in the higher part. These two-class structure per capita distributions are qualitatively similar to income and wealth distributions in many countries of the world, but the fraction of firms per employee within the high-class Pareto is about 49% in sales per employee, and 33% after averaging on the four metrics, whereas in countries the fraction of rich agents in the Pareto zone is less than 10%. The quasi-exponential zone can be adjusted by Gamma or Log-normal distributions. On the other hand, Forbes classifies the G-2000 firms in 82 different industries or economic activities. Within each industry, the wealth distribution per employee also follows a two-class structure, but when the aggregate wealth of firms in each industry for the four metrics is divided by the total number of employees in that industry, then the 82 points of the aggregate wealth distribution by industry per employee can be well adjusted by quasi-exponential curves for the four metrics.
HERA: A New Platform for Embedding Agents in Heterogeneous Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Alonso, Ricardo S.; de Paz, Juan F.; García, Óscar; Gil, Óscar; González, Angélica
Ambient Intelligence (AmI) based systems require the development of innovative solutions that integrate distributed intelligent systems with context-aware technologies. In this sense, Multi-Agent Systems (MAS) and Wireless Sensor Networks (WSN) are two key technologies for developing distributed systems based on AmI scenarios. This paper presents the new HERA (Hardware-Embedded Reactive Agents) platform, that allows using dynamic and self-adaptable heterogeneous WSNs on which agents are directly embedded on the wireless nodes This approach facilitates the inclusion of context-aware capabilities in AmI systems to gather data from their surrounding environments, achieving a higher level of ubiquitous and pervasive computing.
NASA Astrophysics Data System (ADS)
Rezaei, Mohammad Hadi; Menhaj, Mohammad Bagher
2018-01-01
This paper investigates the stationary average consensus problem for a class of heterogeneous-order multi-agent systems. The goal is to bring the positions of agents to the average of their initial positions while letting the other states converge to zero. To this end, three different consensus protocols are proposed. First, based on the auxiliary variables information among the agents under switching directed networks and state-feedback control, a protocol is proposed whereby all the agents achieve stationary average consensus. In the second and third protocols, by resorting to only measurements of relative positions of neighbouring agents under fixed balanced directed networks, two control frameworks are presented with two strategies based on state-feedback and output-feedback control. Finally, simulation results are given to illustrate the effectiveness of the proposed protocols.
Theory of networked minority games based on strategy pattern dynamics.
Lo, T S; Chan, H Y; Hui, P M; Johnson, N F
2004-11-01
We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. An important feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the minority game with connected populations. Expressions for the mean success rate among the agents and for the mean success rate for agents with k neighbors are derived. We also use the theory to estimate the value of connectivity p above which the binary-agent-resource system with high resource levels makes the transition into the high-connectivity state.
Non-equilibrium thermodynamics theory of econometric source discovery for large data analysis
NASA Astrophysics Data System (ADS)
van Bergem, Rutger; Jenkins, Jeffrey; Benachenhou, Dalila; Szu, Harold
2014-05-01
Almost all consumer and firm transactions are achieved using computers and as a result gives rise to increasingly large amounts of data available for analysts. The gold standard in Economic data manipulation techniques matured during a period of limited data access, and the new Large Data Analysis (LDA) paradigm we all face may quickly obfuscate most tools used by Economists. When coupled with an increased availability of numerous unstructured, multi-modal data sets, the impending 'data tsunami' could have serious detrimental effects for Economic forecasting, analysis, and research in general. Given this reality we propose a decision-aid framework for Augmented-LDA (A-LDA) - a synergistic approach to LDA which combines traditional supervised, rule-based Machine Learning (ML) strategies to iteratively uncover hidden sources in large data, the artificial neural network (ANN) Unsupervised Learning (USL) at the minimum Helmholtz free energy for isothermal dynamic equilibrium strategies, and the Economic intuitions required to handle problems encountered when interpreting large amounts of Financial or Economic data. To make the ANN USL framework applicable to economics we define the temperature, entropy, and energy concepts in Economics from non-equilibrium molecular thermodynamics of Boltzmann viewpoint, as well as defining an information geometry, on which the ANN can operate using USL to reduce information saturation. An exemplar of such a system representation is given for firm industry equilibrium. We demonstrate the traditional ML methodology in the economics context and leverage firm financial data to explore a frontier concept known as behavioral heterogeneity. Behavioral heterogeneity on the firm level can be imagined as a firm's interactions with different types of Economic entities over time. These interactions could impose varying degrees of institutional constraints on a firm's business behavior. We specifically look at behavioral heterogeneity for firms that are operating with the label of `Going-Concern' and firms labeled according to institutional influence they may be experiencing, such as constraints on firm hiring/spending while in a Bankruptcy or a Merger procedure. Uncovering invariant features, or behavioral data metrics from observable firm data in an economy can greatly benefit the FED, World Bank, etc. We find that the ML/LDA communities can benefit from Economic intuitions just as much as Economists can benefit from generic data exploration tools. The future of successful Economic data understanding, modeling, simulation, and visualization can be amplified by new A-LDA models and approaches for new and analogous models of Economic system dynamics. The potential benefits of improved economic data analysis and real time decision aid tools are numerous for researchers, analysts, and federal agencies who all deal with increasingly large amounts of complex data to support their decision making.
"Professor" William C. Wilson and his Actina electric pocket battery for curing ocular disease.
Ferry, A P
1998-02-01
To investigate the activities of the firm that manufactured and sold the Actina, the leading example of ophthalmic quackery in the era of the founding of the American Academy of Ophthalmology. Advertisements for the Actina in turn-of-the-century newspapers and magazines were studied, and additional related investigations were undertaken at leading historical societies in the United States and at the headquarters of the American Medical Association. The Actina was widely advertised as a cure for most of life's ills, particularly those of the eye and ear. Its manufacturers claimed that electrical properties were the mechanism of the Actina's alleged therapeutic effects. However, research has shown that the instrument had no electrical properties, its manufacturers had no medical training, and that the Actina was useless as a therapeutic agent. The firm that manufactured the Actina was located in Kansas City and was at the zenith of its success when the first meeting of the American Academy of Ophthalmology was held there in 1896. Its fraudulent activities sparked a continuing public outcry that contributed to the passage of the Pure Food and Drug Act of 1906. The American Medical Association's Investigative Bureau was a major factor in the firm being put out of business in 1915 by the federal government.
Collective learning for the emergence of social norms in networked multiagent systems.
Yu, Chao; Zhang, Minjie; Ren, Fenghui
2014-12-01
Social norms such as social rules and conventions play a pivotal role in sustaining system order by regulating and controlling individual behaviors toward a global consensus in large-scale distributed systems. Systematic studies of efficient mechanisms that can facilitate the emergence of social norms enable us to build and design robust distributed systems, such as electronic institutions and norm-governed sensor networks. This paper studies the emergence of social norms via learning from repeated local interactions in networked multiagent systems. A collective learning framework, which imitates the opinion aggregation process in human decision making, is proposed to study the impact of agent local collective behaviors on the emergence of social norms in a number of different situations. In the framework, each agent interacts repeatedly with all of its neighbors. At each step, an agent first takes a best-response action toward each of its neighbors and then combines all of these actions into a final action using ensemble learning methods. Extensive experiments are carried out to evaluate the framework with respect to different network topologies, learning strategies, numbers of actions, influences of nonlearning agents, and so on. Experimental results reveal some significant insights into the manipulation and control of norm emergence in networked multiagent systems achieved through local collective behaviors.
2018-01-01
An agent-based computer model that builds representative regional U.S. hog production networks was developed and employed to assess the potential impact of the ongoing trend towards increased producer specialization upon network-level resilience to catastrophic disease outbreaks. Empirical analyses suggest that the spatial distribution and connectivity patterns of contact networks often predict epidemic spreading dynamics. Our model heuristically generates realistic systems composed of hog producer, feed mill, and slaughter plant agents. Network edges are added during each run as agents exchange livestock and feed. The heuristics governing agents’ contact patterns account for factors including their industry roles, physical proximities, and the age of their livestock. In each run, an infection is introduced, and may spread according to probabilities associated with the various modes of contact. For each of three treatments—defined by one-phase, two-phase, and three-phase production systems—a parameter variation experiment examines the impact of the spatial density of producer agents in the system upon the length and size of disease outbreaks. Resulting data show phase transitions whereby, above some density threshold, systemic outbreaks become possible, echoing findings from percolation theory. Data analysis reveals that multi-phase production systems are vulnerable to catastrophic outbreaks at lower spatial densities, have more abrupt percolation transitions, and are characterized by less-predictable outbreak scales and durations. Key differences in network-level metrics shed light on these results, suggesting that the absence of potentially-bridging producer–producer edges may be largely responsible for the superior disease resilience of single-phase “farrow to finish” production systems. PMID:29522574
Carney, Timothy Jay; Morgan, Geoffrey P; Jones, Josette; McDaniel, Anna M; Weaver, Michael T; Weiner, Bryan; Haggstrom, David A
2015-10-01
Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. This virtual experiment revealed that patterns of overall network symmetry, agent cohesion, and connectedness varied by community health center performance level. Visual assessment of both the agent-to-agent knowledge sharing network and agent-to-resource knowledge use network diagrams demonstrated that community health centers labeled as high performers typically showed higher levels of collaboration and cohesiveness among agent classes, faster knowledge-absorption rates, and fewer agents that were unconnected to key knowledge resources. Conclusions and research implications: Using the point-in-time survey data outlining community health center cancer-screening practices, our computational model successfully distinguished between high and low performers. Results indicated that high-performance environments displayed distinctive network characteristics in patterns of interaction among agents, as well as in the access and utilization of key knowledge resources. Our study demonstrated how non-network-specific data obtained from a point-in-time survey can be employed to forecast community health center performance over time, thereby enhancing the sustainability of long-term strategic-improvement efforts. Our results revealed a strategic profile for community health center cancer-screening improvement via simulation over a projected 10-year period. The use of computational modeling allows additional inferential knowledge to be drawn from existing data when examining organizational performance in increasingly complex environments. Copyright © 2015 Elsevier Inc. All rights reserved.
Technology, energy and the environment
NASA Astrophysics Data System (ADS)
Mitchell, Glenn Terry
This dissertation consists of three distinct papers concerned with technology, energy and the environment. The first paper is an empirical analysis of production under uncertainty, using agricultural production data from the central United States. Unlike previous work, this analysis identifies the effect of actual realizations of weather as well as farmers' expectations about weather. The results indicate that both of these are significant factors explaining short run profits in agriculture. Expectations about weather, called climate, affect production choices, and actual weather affects realized output. These results provide better understanding of the effect of climate change in agriculture. The second paper examines how emissions taxes induce innovation that reduces pollution. A polluting firm chooses technical improvement to minimize cost over an infinite horizon, given an emission tax set by a planner. This leads to a solution path for technical change. Changes in the tax rate affect the path for innovation. Setting the tax at equal to the marginal damage (which is optimal in a static setting with no technical change) is not optimal in the presence of technical change. When abatement is also available as an alternative to technical change, changes in the tax can have mixed effects, due to substitution effects. The third paper extends the theoretical framework for exploring the diffusion of new technologies. Information about new technologies spreads through the economy by means of a network. The pattern of diffusion will depend on the structure of this network. Observed networks are the result of an evolutionary process. This paper identifies how these evolutionary outcomes compare with optimal solutions. The conditions guaranteeing convergence to an optimal outcome are quite stringent. It is useful to determine the set of initial population states that do converge to an optimal outcome. The distribution of costs and benefits among the agents within an information processing structure plays a critical role in defining this set. These distributional arrangements represent alternative institutional regimes. Institutional changes can improve outcomes, free the flow of information, and encourage the diffusion of profitable new technologies.
Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks
NASA Astrophysics Data System (ADS)
Sadek, Add; Basha, Nagi
Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.
Watson, Richard A; Mills, Rob; Buckley, C L
2011-01-01
In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organize into structures that enhance global adaptation, efficiency, or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology, and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalization, and optimization are well understood. Such global functions within a single agent or organism are not wholly surprising, since the mechanisms (e.g., Hebbian learning) that create these neural organizations may be selected for this purpose; but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviors when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g., when they can influence which other agents they interact with), then, in adapting these inter-agent relationships to maximize their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviors as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalize by idealizing stored patterns and/or creating new combinations of subpatterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviors in the same sense, and by the same mechanism, as with the organizational principles familiar in connectionist models of organismic learning.
Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling
NASA Astrophysics Data System (ADS)
Mitrović, Marija; Tadić, Bosiljka
2012-11-01
We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative emotions (critique). We also demonstrate how the community structure is tuned by varying a relevant parameter in the model. All data used in these works are fully anonymized.
Maturation trajectories of cortical resting-state networks depend on the mediating frequency band.
Khan, Sheraz; Hashmi, Javeria A; Mamashli, Fahimeh; Michmizos, Konstantinos; Kitzbichler, Manfred G; Bharadwaj, Hari; Bekhti, Yousra; Ganesan, Santosh; Garel, Keri-Lee A; Whitfield-Gabrieli, Susan; Gollub, Randy L; Kong, Jian; Vaina, Lucia M; Rana, Kunjan D; Stufflebeam, Steven M; Hämäläinen, Matti S; Kenet, Tal
2018-07-01
The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30 Hz) and gamma (31-80 Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development. Copyright © 2018. Published by Elsevier Inc.
A Financial Market Model Incorporating Herd Behaviour.
Wray, Christopher M; Bishop, Steven R
2016-01-01
Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.
Human-level control through deep reinforcement learning.
Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis
2015-02-26
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Human-level control through deep reinforcement learning
NASA Astrophysics Data System (ADS)
Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis
2015-02-01
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events
Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.
2010-01-01
The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624
Dynamical and topological aspects of consensus formation in complex networks
NASA Astrophysics Data System (ADS)
Chacoma, A.; Mato, G.; Kuperman, M. N.
2018-04-01
The present work analyzes a particular scenario of consensus formation, where the individuals navigate across an underlying network defining the topology of the walks. The consensus, associated to a given opinion coded as a simple message, is generated by interactions during the agent's walk and manifest itself in the collapse of the various opinions into a single one. We analyze how the topology of the underlying networks and the rules of interaction between the agents promote or inhibit the emergence of this consensus. We find that non-linear interaction rules are required to form consensus and that consensus is more easily achieved in networks whose degree distribution is narrower.
An Agent-Based Model of Centralized Institutions, Social Network Technology, and Revolution
Makowsky, Michael D.; Rubin, Jared
2013-01-01
This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change. PMID:24278280
Performance in quasi-firms: an example from the Community Clinical Oncology Program.
Lacey, L M; Hynes, D M; Kaluzny, A D
1992-01-01
In this analysis, the authors examined the effects of different sets of process, structure, and environmental variables on the performance of the CCOP as a quasi-firm. Specifically, they distinguished between internal organizational processes, structural, and size characteristics of the CCOP and the organizational environment created by prior NCI program experience and the relationship within the quasi-firm. The analysis revealed that these sets of organizational and environmental characteristics have differential effects on treatment accrual. The strongest predictors are those associated with the quasi-firm relationship between the CCOP and its chosen research bases. Any definitive policy implications for the design of organizational network relationships--especially the CCOPs--will require further analysis. Particular attention needs to be given to the longitudinal nature of the relationships and the ability of these organizational and environmental factors to affect other aspects of performance. Several points have been made within this initial assessment. First, the structural character of the CCOP and its relationship to its organizational environment are important factors affecting accrual performance. The subtleties of this multivariate model are not as important as simply demonstrating that the various internal and external characteristics of these organizations as quasi-firms simultaneously affect their ability to accrue patients to clinical trials. Secondly, the importance of research base relations, and particularly the significant role of nurses, needs to be emphasized. While CCOPs were originally designed as a network of physicians and hospitals, it appears that an infrastructure of professionally active nurses working within a larger organizational environment is critical to success--at least as defined by accrual to treatment protocols. Finally, the failure of prior experience with other NCI community programs to affect CCOP accrual performance suggests that such experience does not assure "organizational learning" that may enhance performance. This suggests that CCOPs can be designated de novo to maximize performance without necessarily having to undergo a developmental or experiential phase involving community cancer programs to be effective. However, the authors suspect that another method of characterizing experience may produce different results. Further analyses of these data will test these results against other measures of CCOP performance. Specifically, attention will be given to whether this same set of characteristics is predictive of accrual to cancer control research protocols. Similarly, these same organizational characteristics may or may not be associated with other dimensions of CCOP performance such as changes in physician practice patterns and/or levels of institutionalization of the CCOP within its local community.(ABSTRACT TRUNCATED AT 400 WORDS)
Router Agent Technology for Policy-Based Network Management
NASA Technical Reports Server (NTRS)
Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston
2011-01-01
This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.
Hybrid modeling and empirical analysis of automobile supply chain network
NASA Astrophysics Data System (ADS)
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
Trustworthiness as a Limitation on Network Neutrality
2007-01-01
June 24, 2005) (Civil No. 1:05CV01272), available at http://www.usdoj.gov/atr/cases/f209700/209728.htm (alleging that actuarial consulting firms moved...43 David D. Clark, Requirements for a Future Internet: Security as a Case Study , ver. 2.0...general solutions; and several high-profile cases had data re-indentified after release. See Bruce Schneier, Anonymity and the Netflix Dataset
Bayesian Inference for Source Reconstruction: A Real-World Application
2014-09-25
deliberately or acci- dentally . Two examples of operational monitoring sensor networks are the deployment of biological sensor arrays by the Department of...remarkable paper, Cox [16] demonstrated that proba- bility theory, when interpreted as logic, is the only calculus that conforms to a consistent theory...of inference. This demonstration provides the firm logical basis for asserting that probability calculus is the unique quantitative theory of
Distributed Control of a Swarm of Autonomous Unmanned Aerial Vehicles
2003-03-01
wisdom, and love have provided a firm anchor in rough times, and a light in the darkness . “Come to me, all you who are weary and burdened, and I will...time. The light-gray trails represent the area that has been covered in the past 50 timesteps. The dark -gray areas are overlapping areas calculated...during the current timestep. The dark line encloses the total contigu- ous sensor area for this example. Note that while agent 1’s footprint does not
2008-10-01
Japan’s Car Makers Backfires,” The Wall Street Journal, July 20, 2007, p. B1. Council on Competitiveness (2007), “The resilient economy: Integrating...Logistics and Transport Focus, Vol. 4, No. 4, pp. 59-64. Chozick, Amy (2007), “A key strategy of Japan’s car makers backfires,” Wall Street...in developed nations is the utility infrastructure, which in many cases is provided by governments or agents outside the firm. Without electrical
A new class of finite-time nonlinear consensus protocols for multi-agent systems
NASA Astrophysics Data System (ADS)
Zuo, Zongyu; Tie, Lin
2014-02-01
This paper is devoted to investigating the finite-time consensus problem for a multi-agent system in networks with undirected topology. A new class of global continuous time-invariant consensus protocols is constructed for each single-integrator agent dynamics with the aid of Lyapunov functions. In particular, it is shown that the settling time of the proposed new class of finite-time consensus protocols is upper bounded for arbitrary initial conditions. This makes it possible for network consensus problems that the convergence time is designed and estimated offline for a given undirected information flow and a group volume of agents. Finally, a numerical simulation example is presented as a proof of concept.
Distributed robust finite-time nonlinear consensus protocols for multi-agent systems
NASA Astrophysics Data System (ADS)
Zuo, Zongyu; Tie, Lin
2016-04-01
This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.
Water supply pipe dimensioning using hydraulic power dissipation
NASA Astrophysics Data System (ADS)
Sreemathy, J. R.; Rashmi, G.; Suribabu, C. R.
2017-07-01
Proper sizing of the pipe component of water distribution networks play an important role in the overall design of the any water supply system. Several approaches have been applied for the design of networks from an economical point of view. Traditional optimization techniques and population based stochastic algorithms are widely used to optimize the networks. But the use of these approaches is mostly found to be limited to the research level due to difficulties in understanding by the practicing engineers, design engineers and consulting firms. More over due to non-availability of commercial software related to the optimal design of water distribution system,it forces the practicing engineers to adopt either trial and error or experience-based design. This paper presents a simple approach based on power dissipation in each pipeline as a parameter to design the network economically, but not to the level of global minimum cost.
Cultural Geography Model Validation
2010-03-01
the Cultural Geography Model (CGM), a government owned, open source multi - agent system utilizing Bayesian networks, queuing systems, the Theory of...referent determined either from theory or SME opinion. 4. CGM Overview The CGM is a government-owned, open source, data driven multi - agent social...HSCB, validation, social network analysis ABSTRACT: In the current warfighting environment , the military needs robust modeling and simulation (M&S
Pervasive surveillance-agent system based on wireless sensor networks: design and deployment
NASA Astrophysics Data System (ADS)
Martínez, José F.; Bravo, Sury; García, Ana B.; Corredor, Iván; Familiar, Miguel S.; López, Lourdes; Hernández, Vicente; Da Silva, Antonio
2010-12-01
Nowadays, proliferation of embedded systems is enhancing the possibilities of gathering information by using wireless sensor networks (WSNs). Flexibility and ease of installation make these kinds of pervasive networks suitable for security and surveillance environments. Moreover, the risk for humans to be exposed to these functions is minimized when using these networks. In this paper, a virtual perimeter surveillance agent, which has been designed to detect any person crossing an invisible barrier around a marked perimeter and send an alarm notification to the security staff, is presented. This agent works in a state of 'low power consumption' until there is a crossing on the perimeter. In our approach, the 'intelligence' of the agent has been distributed by using mobile nodes in order to discern the cause of the event of presence. This feature contributes to saving both processing resources and power consumption since the required code that detects presence is the only system installed. The research work described in this paper illustrates our experience in the development of a surveillance system using WNSs for a practical application as well as its evaluation in real-world deployments. This mechanism plays an important role in providing confidence in ensuring safety to our environment.
Modelling trading networks and the role of trust
NASA Astrophysics Data System (ADS)
Barrio, Rafael A.; Govezensky, Tzipe; Ruiz-Gutiérrez, Élfego; Kaski, Kimmo K.
2017-04-01
We present a simple dynamical model for describing trading interactions between agents in a social network by considering only two dynamical variables, namely money and goods or services, that are assumed conserved over the whole time span of the agents' trading transactions. A key feature of the model is that agent-to-agent transactions are governed by the price in units of money per goods, which is dynamically changing, and by a trust variable, which is related to the trading history of each agent. All agents are able to sell or buy, and the decision to do either has to do with the level of trust the buyer has in the seller, the price of the goods and the amount of money and goods at the disposal of the buyer. Here we show the results of extensive numerical calculations under various initial conditions in a random network of agents and compare the results with the available related data. In most cases the agreement between the model results and real data turns out to be fairly good, which allow us to draw some general conclusions as how different trading strategies could affect the distribution of wealth in different kinds of societies. Our calculations reveal the striking effects of trust in commercial relations, namely that trust makes trading links more robust and the wealth distribution more even as well as allows for the existence of a healthy middle class.
Consensus positive position feedback control for vibration attenuation of smart structures
NASA Astrophysics Data System (ADS)
Omidi, Ehsan; Nima Mahmoodi, S.
2015-04-01
This paper presents a new network-based approach for active vibration control in smart structures. In this approach, a network with known topology connects collocated actuator/sensor elements of the smart structure to one another. Each of these actuators/sensors, i.e., agent or node, is enhanced by a separate multi-mode positive position feedback (PPF) controller. The decentralized PPF controlled agents collaborate with each other in the designed network, under a certain consensus dynamics. The consensus constraint forces neighboring agents to cooperate with each other such that the disagreement between the time-domain actuation of the agents is driven to zero. The controller output of each agent is calculated using state-space variables; hence, optimal state estimators are designed first for the proposed observer-based consensus PPF control. The consensus controller is numerically investigated for a flexible smart structure, i.e., a thin aluminum beam that is clamped at its both ends. Results demonstrate that the consensus law successfully imposes synchronization between the independently controlled agents, as the disagreements between the decentralized PPF controller variables converge to zero in a short time. The new consensus PPF controller brings extra robustness to vibration suppression in smart structures, where malfunctions of an agent can be compensated for by referencing the neighboring agents’ performance. This is demonstrated in the results by comparing the new controller with former centralized PPF approach.
Autonomic and Coevolutionary Sensor Networking
NASA Astrophysics Data System (ADS)
Boonma, Pruet; Suzuki, Junichi
(WSNs) applications are often required to balance the tradeoffs among conflicting operational objectives (e.g., latency and power consumption) and operate at an optimal tradeoff. This chapter proposes and evaluates a architecture, called BiSNET/e, which allows WSN applications to overcome this issue. BiSNET/e is designed to support three major types of WSN applications: , and hybrid applications. Each application is implemented as a decentralized group of, which is analogous to a bee colony (application) consisting of bees (agents). Agents collect sensor data or detect an event (a significant change in sensor reading) on individual nodes, and carry sensor data to base stations. They perform these data collection and event detection functionalities by sensing their surrounding network conditions and adaptively invoking behaviors such as pheromone emission, reproduction, migration, swarming and death. Each agent has its own behavior policy, as a set of genes, which defines how to invoke its behaviors. BiSNET/e allows agents to evolve their behavior policies (genes) across generations and autonomously adapt their performance to given objectives. Simulation results demonstrate that, in all three types of applications, agents evolve to find optimal tradeoffs among conflicting objectives and adapt to dynamic network conditions such as traffic fluctuations and node failures/additions. Simulation results also illustrate that, in hybrid applications, data collection agents and event detection agents coevolve to augment their adaptability and performance.
Influence of network topology on cooperative problem-solving systems.
Fontanari, José F; Rodrigues, Francisco A
2016-09-01
The idea of a collective intelligence behind the complex natural structures built by organisms suggests that the organization of social networks is selected so as to optimize problem-solving competence at the group level. Here we study the influence of the social network topology on the performance of a group of agents whose task is to locate the global maxima of NK fitness landscapes. Agents cooperate by broadcasting messages informing on their fitness and use this information to imitate the fittest agent in their influence networks. In the case those messages convey accurate information on the proximity of the solution (i.e., for smooth fitness landscapes), we find that high connectivity as well as centralization boosts the group performance. For rugged landscapes, however, these characteristics are beneficial for small groups only. For large groups, it is advantageous to slow down the information transmission through the network to avoid local maximum traps. Long-range links and modularity have marginal effects on the performance of the group, except for a very narrow region of the model parameters.
NASA Astrophysics Data System (ADS)
Wang, Xiao-Jun; An, Long-Xi; Yu, Xu-Tao; Zhang, Zai-Chen
2017-10-01
A multilayer quantum secret sharing protocol based on GHZ state is proposed. Alice has the secret carried by quantum state and wants to distribute this secret to multiple agent nodes in the network. In this protocol, the secret is transmitted and shared layer by layer from root Alice to layered agents. The number of agents in each layer is a geometric sequence with a specific common ratio. By sharing GHZ maximally entangled states and making generalized Bell basis measurement, one qubit state can be distributed to multiparty agents and the secret is shared. Only when all agents at the last layer cooperate together, the secret can be recovered. Compared with other protocols based on the entangled state, this protocol adopts layered construction so that secret can be distributed to more agents with fewer particles GHZ state. This quantum secret sharing protocol can be used in wireless network to ensure the security of information delivery.
Using pullulan-based edible coatings to extend shelf-life of fresh-cut 'Fuji' apples.
Wu, Shengjun; Chen, Jinhua
2013-04-01
Pullulan is a thickener that can form semipermeable films, and glutathione is an effective reducing agent, while chitooligosaccharide has antibacterial activity. In this study, effect of pullulan-based coatings in combination with antibrowning and antibacterial agents (1% pullulan; 0.8% glutathione+1% chitooligosaccharides; and 0.8% glutathione+1% chitooligosaccharides+1% pullulan) on apple slices was investigated during hypothermia storage. Pullulan-coating treatments effectively retarded enzymatic browning, maintained firmness, decreased weight loss, and inhibited microbial growth and respiration rate of apple slices during hypothermia storage compared with that of the control (p<0.05). Results indicate that using pullulan-based coatings in combination with glutathione and chitooligosaccharides is a promising way to extend the shelf-life of apple slices. Copyright © 2013 Elsevier B.V. All rights reserved.
Peng, Tzu-Ju Ann; Lo, Fang-Yi; Lin, Chin-Shien; Yu, Chwo-Ming Joseph
2006-01-01
At issue is whether network resources imply some resources available to all members in networks or available only to those occupying structurally central positions in networks. In this article, two conceptual models, the additive and interaction models of the firm, are empirically tested regarding the impact of hospital resources, network resources, and centrality on hospital performance in the Taiwan health care industry. The results demonstrate that: (1) in the additive model, hospital resources and centrality independently affect performance, whereas network resources do not; and (2) no evidence supports the interaction effect of centrality and resources on performance. Based on our findings in Taiwanese practices, the extent to which the resources are acquired externally from networks, we suggest that while adopting interorganizational strategies, hospitals should clearly identify those important resources that reside in-house and those transferred from network partners. How hospitals access resources from central positions is more important than what network resources can hospitals acquire from networks. Hospitals should improve performance by exploiting its in-house resources rather than obtaining network resources externally. In addition, hospitals should not only invest in hospital resources for better performance but should also move to central positions in networks to benefit from collaborations.
Agent-Based Chemical Plume Tracing Using Fluid Dynamics
NASA Technical Reports Server (NTRS)
Zarzhitsky, Dimitri; Spears, Diana; Thayer, David; Spears, William
2004-01-01
This paper presents a rigorous evaluation of a novel, distributed chemical plume tracing algorithm. The algorithm is a combination of the best aspects of the two most popular predecessors for this task. Furthermore, it is based on solid, formal principles from the field of fluid mechanics. The algorithm is applied by a network of mobile sensing agents (e.g., robots or micro-air vehicles) that sense the ambient fluid velocity and chemical concentration, and calculate derivatives. The algorithm drives the robotic network to the source of the toxic plume, where measures can be taken to disable the source emitter. This work is part of a much larger effort in research and development of a physics-based approach to developing networks of mobile sensing agents for monitoring, tracking, reporting and responding to hazardous conditions.
KODAMA and VPC based Framework for Ubiquitous Systems and its Experiment
NASA Astrophysics Data System (ADS)
Takahashi, Kenichi; Amamiya, Satoshi; Iwao, Tadashige; Zhong, Guoqiang; Kainuma, Tatsuya; Amamiya, Makoto
Recently, agent technologies have attracted a lot of interest as an emerging programming paradigm. With such agent technologies, services are provided through collaboration among agents. At the same time, the spread of mobile technologies and communication infrastructures has made it possible to access the network anytime and from anywhere. Using agents and mobile technologies to realize ubiquitous computing systems, we propose a new framework based on KODAMA and VPC. KODAMA provides distributed management mechanisms by using the concept of community and communication infrastructure to deliver messages among agents without agents being aware of the physical network. VPC provides a method of defining peer-to-peer services based on agent communication with policy packages. By merging the characteristics of both KODAMA and VPC functions, we propose a new framework for ubiquitous computing environments. It provides distributed management functions according to the concept of agent communities, agent communications which are abstracted from the physical environment, and agent collaboration with policy packages. Using our new framework, we conducted a large-scale experiment in shopping malls in Nagoya, which sent advertisement e-mails to users' cellular phones according to user location and attributes. The empirical results showed that our new framework worked effectively for sales in shopping malls.
ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation
NASA Astrophysics Data System (ADS)
Matsuyama, Shinako; Terano, Takao
This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.
Consensus in evolving networks of mobile agents
NASA Astrophysics Data System (ADS)
Baronchelli, Andrea; Díaz-Guilera, Albert
2012-02-01
Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving networks defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this talk can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.
Consensus in networks of mobile communicating agents
NASA Astrophysics Data System (ADS)
Baronchelli, Andrea; Díaz-Guilera, Albert
2012-01-01
Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving network defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this paper can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.
Analyzing phase diagrams and phase transitions in networked competing populations
NASA Astrophysics Data System (ADS)
Ni, Y.-C.; Yin, H. P.; Xu, C.; Hui, P. M.
2011-03-01
Phase diagrams exhibiting the extent of cooperation in an evolutionary snowdrift game implemented in different networks are studied in detail. We invoke two independent payoff parameters, unlike a single payoff often used in most previous works that restricts the two payoffs to vary in a correlated way. In addition to the phase transition points when a single payoff parameter is used, phase boundaries separating homogeneous phases consisting of agents using the same strategy and a mixed phase consisting of agents using different strategies are found. Analytic expressions of the phase boundaries are obtained by invoking the ideas of the last surviving patterns and the relative alignments of the spectra of payoff values to agents using different strategies. In a Watts-Strogatz regular network, there exists a re-entrant phenomenon in which the system goes from a homogeneous phase into a mixed phase and re-enters the homogeneous phase as one of the two payoff parameters is varied. The non-trivial phase diagram accompanying this re-entrant phenomenon is quantitatively analyzed. The effects of noise and cooperation in randomly rewired Watts-Strogatz networks are also studied. The transition between a mixed phase and a homogeneous phase is identify to belong to the directed percolation universality class. The methods used in the present work are applicable to a wide range of problems in competing populations of networked agents.
Emergent inequality and self-organized social classes in a network of power and frustration
Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano
2017-02-17
We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution ofmore » wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.« less
Emergent inequality and self-organized social classes in a network of power and frustration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano
We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution ofmore » wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.« less
Emergent inequality and self-organized social classes in a network of power and frustration
Mahault, Benoit; Saxena, Avadh
2017-01-01
We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes. PMID:28212440
Stochastic opinion formation in scale-free networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
M. Bartolozzi; D. B. Leinweber; A. W. Thomas
2005-10-01
The dynamics of opinion formation in large groups of people is a complex nonlinear phenomenon whose investigation is just beginning. Both collective behavior and personal views play an important role in this mechanism. In the present work we mimic the dynamics of opinion formation of a group of agents, represented by two states 1, as a stochastic response of each agent to the opinion of his/her neighbors in the social network and to feedback from the average opinion of the whole. In the light of recent studies, a scale-free Barabsi-Albert network has been selected to simulate the topology of themore » interactions. A turbulent-like dynamics, characterized by an intermittent behavior, is observed for a certain range of the model parameters. The problem of uncertainty in decision taking is also addressed both from a topological point of view, using random and targeted removal of agents from the network, and by implementing a three-state model, where the third state, zero, is related to the information available to each agent. Finally, the results of the model are tested against the best known network of social interactions: the stock market. A time series of daily closures of the Dow-Jones index has been used as an indicator of the possible applicability of our model in the financial context. Good qualitative agreement is found.« less
Emergent inequality and self-organized social classes in a network of power and frustration.
Mahault, Benoit; Saxena, Avadh; Nisoli, Cristiano
2017-01-01
We propose a simple agent-based model on a network to conceptualize the allocation of limited wealth among more abundant expectations at the interplay of power, frustration, and initiative. Concepts imported from the statistical physics of frustrated systems in and out of equilibrium allow us to compare subjective measures of frustration and satisfaction to collective measures of fairness in wealth distribution, such as the Lorenz curve and the Gini index. We find that a completely libertarian, law-of-the-jungle setting, where every agent can acquire wealth from or lose wealth to anybody else invariably leads to a complete polarization of the distribution of wealth vs. opportunity. This picture is however dramatically ameliorated when hard constraints are imposed over agents in the form of a limiting network of transactions. There, an out of equilibrium dynamics of the networks, based on a competition between power and frustration in the decision-making of agents, leads to network coevolution. The ratio of power and frustration controls different dynamical regimes separated by kinetic transitions and characterized by drastically different values of equality. It also leads, for proper values of social initiative, to the emergence of three self-organized social classes, lower, middle, and upper class. Their dynamics, which appears mostly controlled by the middle class, drives a cyclical regime of dramatic social changes.
An Intelligent Pinger Network for Solid Glacier Environments
NASA Astrophysics Data System (ADS)
Schönitz, S.; Reuter, S.; Henke, C.; Jeschke, S.; Ewert, D.; Eliseev, D.; Heinen, D.; Linder, P.; Scholz, F.; Weinstock, L.; Wickmann, S.; Wiebusch, C.; Zierke, S.
2016-12-01
This talk presents a novel approach for an intelligent, agent-based pinger network in an extraterrestrial glacier environment. Because of recent findings of the Cassini spacecraft, a mission to Saturn's moon Enceladus is planned in order search for extraterrestrial life within the ocean beneath Enceladus' ice crust. Therefore, a maneuverable melting probe, the EnEx probe, was developed to melt into Enceladus' ice and take liquid samples from water-filled crevasses. Hence, the probe collecting the samples has to be able to navigate in ice which is a hard problem, because neither visual nor gravitational methods can be used. To enhance the navigability of the probe, a network of autonomous pinger units (APU) is in development that is able to extract a map of the ice environment via ultrasonic soundwaves. A network of these APUs will be deployed on the surface of Enceladus, melt into the ice and form a network to help guide the probe safely to its destination. The APU network is able to form itself fully autonomously and to compensate system failures of individual APUs. The agents controlling the single APU are realized by rule-based expert systems implemented in CLIPS. The rule-based expert system evaluates available information of the environment, decides for actions to take to achieve the desired goal (e.g. a specific network topology), and executes and monitors such actions. In general, it encodes certain situations that are evaluated whenever an APU is currently idle, and then decides for a next action to take. It bases this decision on its internal world model that is shared with the other APUs. The optimal network topology that defines each agents position is iteratively determined by mixed-integer nonlinear programming. Extensive simulations studies show that the proposed agent design enables the APUs to form a robust network topology that is suited to create a reliable 3D map of the ice environment.
Fu, Wei; Watanabe, Yurika; Inoue, Keita; Moriguchi, Natsumi; Fusa, Kazunao; Yanagisawa, Yuya; Mutoh, Takaaki; Nakamura, Takashi
2018-04-15
The effect of pre-cooked cheeses of different emulsifying conditions on the viscosities, mechanical properties, fat globules, and microstructure of processed cheese was investigated, and changes in protein network relating to the creaming effect and the occurrence of yielding point were discussed. The addition of pre-cooked cheeses with a short stirring time had no obvious impact on the fat globules and protein network. The random network brought low viscosities and a gradual increase in the fracture stress/strain curve. The addition of pre-cooked cheeses with the long stirring time caused protein network to become fine-stranded. The fine-stranded network caused creaming effect, and brought yielding points in the mechanical properties. The pre-cooked cheese with the small fat globules also caused fat globules to become smaller, and give the processed cheese more firmness. This study provides a potential solution to control the functional properties of processed cheese by using a variety of pre-cooked cheeses. Copyright © 2017 Elsevier Ltd. All rights reserved.
The Community Structure of the European Network of Interlocking Directorates 2005–2010
Heemskerk, Eelke M.; Daolio, Fabio; Tomassini, Marco
2013-01-01
The boards of directors at large European companies overlap with each other to a sizable extent both within and across national borders. This could have important economic, political and management consequences. In this work we study in detail the topological structure of the networks that arise from this phenomenon. Using a comprehensive information database, we reconstruct the implicit networks of shared directorates among the top 300 European firms in 2005 and 2010, and suggest a number of novel ways to explore the trans-nationality of such business elite networks. Powerful community detection heuristics indicate that geography still plays an important role: there exist clear communities and they have a distinct national character. Nonetheless, from 2005 to 2010 we observe a densification of the boards interlocks network and a larger transnational orientation in its communities. Together with central actors and assortativity analyses, we provide statistical evidence that, at the level of corporate governance, Europe is getting closer. PMID:23894318
The community structure of the European network of interlocking directorates 2005-2010.
Heemskerk, Eelke M; Daolio, Fabio; Tomassini, Marco
2013-01-01
The boards of directors at large European companies overlap with each other to a sizable extent both within and across national borders. This could have important economic, political and management consequences. In this work we study in detail the topological structure of the networks that arise from this phenomenon. Using a comprehensive information database, we reconstruct the implicit networks of shared directorates among the top 300 European firms in 2005 and 2010, and suggest a number of novel ways to explore the trans-nationality of such business elite networks. Powerful community detection heuristics indicate that geography still plays an important role: there exist clear communities and they have a distinct national character. Nonetheless, from 2005 to 2010 we observe a densification of the boards interlocks network and a larger transnational orientation in its communities. Together with central actors and assortativity analyses, we provide statistical evidence that, at the level of corporate governance, Europe is getting closer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Neil, Joshua Charles; Fisk, Michael Edward; Brugh, Alexander William
A system, apparatus, computer-readable medium, and computer-implemented method are provided for detecting anomalous behavior in a network. Historical parameters of the network are determined in order to determine normal activity levels. A plurality of paths in the network are enumerated as part of a graph representing the network, where each computing system in the network may be a node in the graph and the sequence of connections between two computing systems may be a directed edge in the graph. A statistical model is applied to the plurality of paths in the graph on a sliding window basis to detect anomalousmore » behavior. Data collected by a Unified Host Collection Agent ("UHCA") may also be used to detect anomalous behavior.« less
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-07-01
This work concerns the study of the effects felt by a network as a whole when a specific node is perturbed. Many real world systems can be described by network models in which the interactions of the various agents can be represented as an edge of a graph. With a graph model in hand, it is possible to evaluate the effect of deleting some of its edges on the architecture and values of nodes of the network. Eventually a node may end up isolated from the rest of the network and an interesting problem is to have a quantitative measure of the impact of such an event. For instance, in the field of finance, the network models are very popular and the proposed methodology allows to carry out "what if" tests in terms of weakening the links between the economic agents, represented as nodes. The two main concepts employed in the proposed methodology are (i) the vibrational IC-Information Centrality, which can provide a measure of the relative importance of a particular node in a network and (ii) autocatalytic networks that can indicate the evolutionary trends of the network. Although these concepts were originally proposed in the context of other fields of knowledge, they were also found to be useful in analyzing financial networks. In order to illustrate the applicability of the proposed methodology, a case of study using the actual data comprising stock market indices of 12 countries is presented.
Stidham, R W; Lee, T C H; Higgins, P D R; Deshpande, A R; Sussman, D A; Singal, A G; Elmunzer, B J; Saini, S D; Vijan, S; Waljee, A K
2014-04-01
Antibodies against tumour necrosis factor-alpha (anti-TNF) are effective therapies in the treatment of ulcerative colitis (UC), but their comparative efficacy is unknown. To perform a network meta-analysis comparing the efficacy of anti-TNF agents in UC. After screening 506 studies, reviewers extracted information on seven studies. Traditional meta-analysis (TMA) was used to compare each anti-TNF agent to placebo. Bayesian network meta-analysis (NMA) was performed to compare the effects of anti-TNF agents to placebo. In addition, sample sizes for comparative efficacy trials were calculated. Compared to placebo, TMA revealed that anti-TNF agents result in a higher likelihood of induction of remission and response (RR: 2.45, 95% CI: 1.72-3.47 and RR: 1.65, 95% CI: 1.37-1.99 respectively) as well as maintenance of remission and response (RR: 2.00, 95% CI: 1.52-2.62 and RR: 1.76, 95% CI: 1.46-2.14 respectively). Individually, infliximab, adalimumab and goliumumab resulted in a higher likelihood of induction and maintenance for both remission and response. NMA found nonsignificant trends in comparisons of the individual agents. The required sample sizes for direct head-to-head trials between infliximab and adalimumab for induction and maintenance are 174 and 204 subjects respectively. This study demonstrates that, compared to placebo, infliximab, adalimumab and golimumab are all effective for the induction and maintenance of remission in ulcerative colitis. However, network meta-analysis demonstrates that no single agent is clinically superior to the others and therefore, other factors such as cost, safety, route of administration and patient preference should dictate our choice of anti-TNF agents. A randomised comparative efficacy trial between infliximab and adalimumab in UC is of practical size and should be performed. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Dewantara, Fauzi; Budianto, Emil
2018-04-01
Chitosan-methyl cellulose semi-IPN hydrogel is used as floating drug delivery system, and calcium carbonate also added as pore forming agent. The hydrogel network arranged by not only using biopolymer chitosan and methyl cellulose, but also the crosslink agent that is glutaraldehyde. Amoxicillin trihydrate entrapped into the polymer network with two different method, in situ loading and post loading. Furthermore both method has been tested for drug entrapment efficiency along with drug dissolution test, and the result for drug entrapment efficiency is in situ loading method has highest value of 100%, compared to post loading method which has value only 71%. Moreover, at the final time of drug dissolution test shows in situ loading method has value of 96% for total accumulative of drug dissolution, meanwhile post loading method has 72%. The value of drug dissolution test from both method is used for analyzing drug dissolution mechanism of amoxicillin trihydrate from hydrogel network with four mathematical drug mechanism models as parameter. The polymer network encounter destructive degradation causes by acid solution which used as dissolution medium, and the level of degradation is observed with optical microscope. However the result shows that degradation of the polymer network doesn't affect drug dissolution mechanism directly. Although the pore forming agent causes the pore inside the hydrogel network create interconnection and it was quite influential to drug dissolution mechanism. Interconnected pore is observed with Scanning Electron Microscope (SEM) and shows that the amount and area of interconnected pore inside the hydrogel network is increasing as drug dissolution goes on.
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.
System and method for secure group transactions
Goldsmith, Steven Y [Rochester, MN
2006-04-25
A method and a secure system, processing on one or more computers, provides a way to control a group transaction. The invention uses group consensus access control and multiple distributed secure agents in a network environment. Each secure agent can organize with the other secure agents to form a secure distributed agent collective.
NASA Astrophysics Data System (ADS)
Yang, Hongyong; Han, Fujun; Zhao, Mei; Zhang, Shuning; Yue, Jun
2017-08-01
Because many networked systems can only be characterized with fractional-order dynamics in complex environments, fractional-order calculus has been studied deeply recently. When diverse individual features are shown in different agents of networked systems, heterogeneous fractional-order dynamics will be used to describe the complex systems. Based on the distinguishing properties of agents, heterogeneous fractional-order multi-agent systems (FOMAS) are presented. With the supposition of multiple leader agents in FOMAS, distributed containment control of FOMAS is studied in directed weighted topologies. By applying Laplace transformation and frequency domain theory of the fractional-order operator, an upper bound of delays is obtained to ensure containment consensus of delayed heterogenous FOMAS. Consensus results of delayed FOMAS in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.
Emergence of Leadership in Communication.
Allahverdyan, Armen E; Galstyan, Aram
2016-01-01
We study a neuro-inspired model that mimics a discussion (or information dissemination) process in a network of agents. During their interaction, agents redistribute activity and network weights, resulting in emergence of leader(s). The model is able to reproduce the basic scenarios of leadership known in nature and society: laissez-faire (irregular activity, weak leadership, sizable inter-follower interaction, autonomous sub-leaders); participative or democratic (strong leadership, but with feedback from followers); and autocratic (no feedback, one-way influence). Several pertinent aspects of these scenarios are found as well-e.g., hidden leadership (a hidden clique of agents driving the official autocratic leader), and successive leadership (two leaders influence followers by turns). We study how these scenarios emerge from inter-agent dynamics and how they depend on behavior rules of agents-in particular, on their inertia against state changes.
Research on mixed network architecture collaborative application model
NASA Astrophysics Data System (ADS)
Jing, Changfeng; Zhao, Xi'an; Liang, Song
2009-10-01
When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.
Designing of Roaming Protocol for Bluetooth Equipped Multi Agent Systems
NASA Astrophysics Data System (ADS)
Subhan, Fazli; Hasbullah, Halabi B.
Bluetooth is an established standard for low cost, low power, wireless personal area network. Currently, Bluetooth does not support any roaming protocol in which handoff occurs dynamically when a Bluetooth device is moving out of the piconet. If a device is losing its connection to the master device, no provision is made to transfer it to another master. Handoff is not possible in a piconet, as in order to stay within the network, a slave would have to keep the same master. So, by definition intra-handoff is not possible within a piconet. This research mainly focuses on Bluetooth technology and designing a roaming protocol for Bluetooth equipped multi agent systems. A mathematical model is derived for an agent. The idea behind the mathematical model is to know when to initiate the roaming process for an agent. A desired trajectory for the agent is calculated using its x and y coordinates system, and is simulated in SIMULINK. Various roaming techniques are also studied and discussed. The advantage of designing a roaming protocol is to ensure the Bluetooth enabled roaming devices can freely move inside the network coverage without losing its connection or break of service in case of changing the base stations.
Evolution of public opinions in closed societies influenced by broadcast media
NASA Astrophysics Data System (ADS)
Fan, Kangqi; Pedrycz, Witold
2017-04-01
Studies on opinion evolution in a closed society can help people design strategies to emancipate from the control of public opinions and prevent the diffusion of extremism. In this work, the social judgment based opinion (SJBO) dynamics model is extended to explore the collective debates in a closed system that consists of a social network and a broadcast network. The broadcast network is a group of channels through which the so-called broadcast media or mainstream media transmit the same opinion to social agents. Numerical experiments show that the broadcast media can assimilate most of the agents when contrarians are absent. Including agents' diverse attitudes toward the broadcast media, although downsizes the supporters of broadcast media, fails to make contrarians outnumber the supporters. The dominance of broadcast media in a closed system can be overturned by introducing a small number of inflexible contrarians. Influenced by the competition between contrarians and broadcast media, few centrists survive the collective debates. The scale of supporters is maximized when agents neither have their own initial opinions nor have access to the contrarians, whereas the development of contrarians can be boosted when agents start with non-zero opinions and the repulsion to broadcast media is taken into consideration.
Wong, Michael K.; Wang, Xufang; Chulikavit, Maruit J.; Liu, Zhimei
2013-01-01
Background In 2006, the economic burden of metastatic renal cell carcinoma (mRCC) was estimated to be up to $1.6 billion worldwide and has since grown annually. With the continuing increase of the economic burden of this disease in the United States, there is a growing need for economic analyses to guide treatment and policy decisions for this patient population. Objective To evaluate available comparative economic data on targeted therapies for patients with mRCC who have failed first-line targeted therapies. Method A broad and comprehensive literature review was conducted of US-based studies between January 1, 2005, and February 11, 2013, evaluating comparative economic evidence for targeted agents that are used as second-line therapy or beyond. Based on the specific search parameters that focused on cost-effectiveness and economic comparisons between vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFr) inhibitors and mammalian target of rapamycin (mTOR) inhibitors, only 7 relevant, US-based economic evaluations were found appropriate for inclusion in the analysis. All authors, who are experts in the health economics and outcomes research field, reviewed the search results. Studies of interest were those with a targeted agent, VEGF/VEGFr or mTOR inhibitor, in at least 1 study arm. Discussion As a group, targeted therapies were found to be cost-effective options in treating patients with refractory mRCC in the United States. Oral therapies showed an economic advantage over intravenous agents, presumably because oral therapies have a lower impact on outpatient resources. Based on 3 studies, everolimus has been shown to have an economic advantage over temsirolimus and to be cost-effective compared with sorafenib. No economic comparison between everolimus and axitinib, the only 2 drugs with a National Comprehensive Cancer Network category 1 recommendation for use after the failure of VEGFr tyrosine kinase inhibitors, is available. Conclusion The limited and heterogeneous sum of the currently available economic evidence does not allow firm conclusions to be drawn about the most cost-effective targeted treatment option in the second-line setting and beyond in patients with mRCC. It is hoped that ongoing head-to-head therapeutic trials and biomarker studies will help improve the economic efficiency of these expensive agents. PMID:24991363
Wang, Na; Zeng, Jiwen
2017-03-17
Wireless sensor networks are deployed to monitor the surrounding physical environments and they also act as the physical environments of parasitic sensor networks, whose purpose is analyzing the contextual privacy and obtaining valuable information from the original wireless sensor networks. Recently, contextual privacy issues associated with wireless communication in open spaces have not been thoroughly addressed and one of the most important challenges is protecting the source locations of the valuable packages. In this paper, we design an all-direction random routing algorithm (ARR) for source-location protecting against parasitic sensor networks. For each package, the routing process of ARR is divided into three stages, i.e., selecting a proper agent node, delivering the package to the agent node from the source node, and sending it to the final destination from the agent node. In ARR, the agent nodes are randomly chosen in all directions by the source nodes using only local decisions, rather than knowing the whole topology of the networks. ARR can control the distributions of the routing paths in a very flexible way and it can guarantee that the routing paths with the same source and destination are totally different from each other. Therefore, it is extremely difficult for the parasitic sensor nodes to trace the packages back to the source nodes. Simulation results illustrate that ARR perfectly confuses the parasitic nodes and obviously outperforms traditional routing-based schemes in protecting source-location privacy, with a marginal increase in the communication overhead and energy consumption. In addition, ARR also requires much less energy than the cloud-based source-location privacy protection schemes.
Hogg, Rachel A; Varda, Danielle
2016-11-01
Community networks that include nonprofit, public, and private organizations have formed around many health issues, such as chronic disease management and healthy living and eating. Despite the increases in the numbers of and funding for cross-sector networks, and the growing literature about them, there are limited data and methods that can be used to assess their effectiveness and analyze their designs. We addressed this gap in knowledge by analyzing the characteristics of 260 cross-sector community health networks that collectively consisted of 7,816 organizations during the period 2008-15. We found that nonprofit organizations were more prevalent than private firms or government agencies in these networks. Traditional types of partners in community health networks such as hospitals, community health centers, and public health agencies were the most trusted and valued by other members of their networks. However, nontraditional partners, such as employer or business groups and colleges or universities, reported contributing relatively high numbers of resources to their networks. Further evidence is needed to inform collaborative management processes and policies as a mechanism for building what the Robert Wood Johnson Foundation describes as a culture of health. Project HOPE—The People-to-People Health Foundation, Inc.
Autonomous sensor manager agents (ASMA)
NASA Astrophysics Data System (ADS)
Osadciw, Lisa A.
2004-04-01
Autonomous sensor manager agents are presented as an algorithm to perform sensor management within a multisensor fusion network. The design of the hybrid ant system/particle swarm agents is described in detail with some insight into their performance. Although the algorithm is designed for the general sensor management problem, a simulation example involving 2 radar systems is presented. Algorithmic parameters are determined by the size of the region covered by the sensor network, the number of sensors, and the number of parameters to be selected. With straight forward modifications, this algorithm can be adapted for most sensor management problems.
Competitive game theoretic optimal routing in optical networks
NASA Astrophysics Data System (ADS)
Yassine, Abdulsalam; Kabranov, Ognian; Makrakis, Dimitrios
2002-09-01
Optical transport service providers need control and optimization strategies for wavelength management, network provisioning, restoration and protection, allowing them to define and deploy new services and maintain competitiveness. In this paper, we investigate a game theory based model for wavelength and flow assignment in multi wavelength optical networks, consisting of several backbone long-haul optical network transport service providers (TSPs) who are offering their services -in terms of bandwidth- to Internet service providers (ISPs). The ISPs act as brokers or agents between the TSP and end user. The agent (ISP) buys services (bandwidth) from the TSP. The TSPs compete among themselves to sell their services and maintain profitability. We present a case study, demonstrating the impact of different bandwidth broker demands on the supplier's profit and the price paid by the network broker.
Behavioral networks as a model for intelligent agents
NASA Technical Reports Server (NTRS)
Sliwa, Nancy E.
1990-01-01
On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs.
A statistical physics approach to scale-free networks and their behaviors
NASA Astrophysics Data System (ADS)
Wu, Fang
This thesis studies five problems of network properties from a unified local-to-global viewpoint of statistical physics: (1) We propose an algorithm that allows the discovery of communities within graphs of arbitrary size, based on Kirchhoff theory of electric networks. Its time complexity scales linearly with the network size. We additionally show how this algorithm allows for the swift discovery of the community surrounding a given node without having to extract all the communities out of a graph. (2) We present a dynamical theory of opinion formation that takes explicitly into account the structure of the social network in which individuals are embedded. We show that the weighted fraction of the population that holds a certain opinion is a martingale. We show that the importance of a given node is proportional to its degree. We verify our predictions by simulations. (3) We show that, when the information transmissibility decays with distance, the epidemic spread on a scale-free network has a finite threshold. We test our predictions by measuring the spread of messages in an organization and by numerical experiments. (4) Suppose users can switch between two behaviors when entering a queueing system: one that never restarts an initial request and one that restarts infinitely often. We show the existence of two thresholds. When the system load is below the lower threshold, it is always better off to be impatient. When above, it is always better off to be patient. Between the two thresholds there exists a homogeneous Nash equilibrium with non-trivial properties. We obtain exact solutions for the two thresholds. (5) We study the endogenous dynamics of reputations in a system consisting of firms with long horizons that provide services with varying levels of quality, and customers who assign to them reputations on the basis of the quality levels that they experience when interacting with them. We show that the dynamics can lead to either well defined equilibria or persistent nonlinear oscillations in the number of customers visiting a firm, implying unstable reputations. We establish the stable criteria.
Novel Holistic Approaches for Overcoming Therapy Resistance in Pancreatic and Colon Cancers.
Sarkar, Fazlul H
2016-01-01
Gastrointestinal (GI) cancers, such as of the colon and pancreas, are highly resistant to both standard and targeted therapeutics. Therapy-resistant and heterogeneous GI cancers harbor highly complex signaling networks (the resistome) that resist apoptotic programming. Commonly used gemcitabine or platinum-based regimens fail to induce meaningful (i.e. disease-reversing) perturbations in the resistome, resulting in high rates of treatment failure. The GI cancer resistance networks are, in part, due to interactions between parallel signaling and aberrantly expressed microRNAs (miRNAs) that collectively promote the development and survival of drug-resistant cancer stem cells with epithelial-to-mesenchymal transition (EMT) characteristics. The lack of understanding of the resistance networks associated with this subpopulation of cells as well as reductionist, single protein-/pathway-targeted approaches have made 'effective drug design' a difficult task. We propose that the successful design of novel therapeutic regimens to target drug-resistant GI tumors is only possible if network-based drug avenues and agents, in particular 'natural agents' with no known toxicity, are correctly identified. Natural agents (dietary agents or their synthetic derivatives) can individually alter miRNA profiles, suppress EMT pathways and eliminate cancer stem-like cells that derive from pancreatic cancer and colon cancer, by partially targeting multiple yet meaningful networks within the GI cancer resistome. However, the efficacy of these agents as combinations (e.g. consumed in the diet) against this resistome has never been studied. This short review article provides an overview of the different challenges involved in the understanding of the GI resistome, and how novel computational biology can help in the design of effective therapies to overcome resistance. © 2015 S. Karger AG, Basel.
ERIC Educational Resources Information Center
Geng, Diane
2008-01-01
Most university students in China have their sights firmly set on future job and study opportunities in urban cities and abroad. However, a network of student volunteers felt compelled to join the cause of rural development and villager empowerment, reminiscent of efforts promoted forty years ago by Chairman Mao who sent "educated youth"…
Energy Security: Reducing Vulnerabilities to Global Energy Networks
2009-03-01
plug-in hybrid vehicles, promote renewable energy sources, invest in low- emission coal plants , advance technologies in bio-fuels, and begin the...Zhongyuan Petroleum Prospecting, a subsidiary of the China Petrochemical Corporation, is the primary oil firm operating in Gambella. Nigeria is the...of the global warming issues and the burning of oil, in particular, is blamed for about 42 percent of the CO2 emissions . 31 Left unchecked, the
THE BRAIN (The Harvard Experimental Basic Reckoning and Instructional Network)
1968-10-01
shown to be flexible enough to be serviceable, at least initially, for most users. As the user grows in experience and his programs in...and firmly established of the two. The advance of science has been marked by a progressive and rapidly accelerating separation of observable...impossible for them to distinguish incorrect reasoning or calculation from errors in graphing. " The bridge crossed, the instrument grows more
Zhang, J; Tong, L; Lamberson, P J; Durazo-Arvizu, R A; Luke, A; Shoham, D A
2015-01-01
The prevalence of adolescent overweight and obesity (hereafter, simply "overweight") in the US has increased over the past several decades. Individually-targeted prevention and treatment strategies targeting individuals have been disappointing, leading some to propose leveraging social networks to improve interventions. We hypothesized that social network dynamics (social marginalization; homophily on body mass index, BMI) and the strength of peer influence would increase or decrease the proportion of network member (agents) becoming overweight over a simulated year, and that peer influence would operate differently in social networks with greater overweight. We built an agent-based model (ABM) using results from R-SIENA. ABMs allow for the exploration of potential interventions using simulated agents. Initial model specifications were drawn from Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health). We focused on a single saturation school with complete network and BMI data over two waves (n = 624). The model was validated against empirical observations at Wave 2. We focused on overall overweight prevalence after a simulated year. Five experiments were conducted: (1) changing attractiveness of high-BMI agents; (2) changing homophily on BMI; (3) changing the strength of peer influence; (4) shifting the overall BMI distribution; and (5) targeting dietary interventions to highly connected individuals. Increasing peer influence showed a dramatic decrease in the prevalence of overweight; making peer influence negative (i.e., doing the opposite of friends) increased overweight. However, the effect of peer influence varied based on the underlying distribution of BMI; when BMI was increased overall, stronger peer influence increased proportion of overweight. Other interventions, including targeted dieting, had little impact. Peer influence may be a viable target in overweight interventions, but the distribution of body size in the population needs to be taken into account. In low-obesity populations, strengthening peer influence may be a useful strategy. Copyright © 2014 Elsevier Ltd. All rights reserved.
Zhang, J; Tong, L; Lamberson, PJ; Durazo, R; Luke, A; Shoham, DA
2014-01-01
The prevalence of adolescent overweight and obesity (hereafter, simply “overweight”) in the US has increased over the past several decades. Individually-targeted prevention and treatment strategies targeting individuals have been disappointing, leading some to propose leveraging social networks to improve interventions. We hypothesized that social network dynamics (social marginalization; homophily on body mass index, BMI) and the strength of peer influence would increase or decrease the proportion of network member (agents) becoming overweight over a simulated year, and that peer influence would operate differently in social networks with greater overweight. We built an agent-based model (ABM) using results from R-SIENA. ABMs allow for the exploration of potential interventions using simulated agents. Initial model specifications were drawn from Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health). We focused on a single saturation school with complete network and BMI data over two waves (n=624). The model was validated against empirical observations at Wave 2. We focused on overall overweight prevalence after a simulated year. Five experiments were conducted: (1) changing attractiveness of high-BMI agents; (2) changing homophily on BMI; (3) changing the strength of peer influence; (4) shifting the overall BMI distribution; and (5) targeting dietary interventions to highly connected individuals. Increasing peer influence showed a dramatic decrease in the prevalence of overweight; making peer influence negative (ie, doing the opposite of friends) increased overweight. However, the effect of peer influence varied based on the underlying distribution of BMI; when BMI was increased overall, stronger peer influence increased proportion of overweight. Other interventions, including targeted dieting, had little impact. Peer influence may be a viable target in overweight interventions, but the distribution of body size in the population needs to be taken into account. In low-obesity populations, strengthening peer influence may be a useful strategy. PMID:24951404
A New HIV Prevention Network Approach: Sociometric Peer Change Agent Selection
Schneider, John A.; Zhou, A. Ning; Laumann, Edward O.
2014-01-01
Internationally, the Peer Change Agent (PCA) model is the most frequently used conceptual framework for HIV prevention. Change agents themselves can be more important than the messages they convey. PCA selection is operationalized via heterogeneous methods based upon individual-level attributes. A sociometric position selection strategy, however, could increase peer influence potency and halt transmission at key network locations. In this study, we selected candidate PCAs based upon relative sociometric bridging and centrality scores and assessed their attributes in comparison to one another and to existing peer educators. We focused upon an emerging HIV epidemic among men who have sex with men in Southern India in 2011. PCAs selected based on their bridging score were more likely to be innovators when compared to other centrally-located PCAs, to PCAs located on the periphery, and to existing peer educators. We also found that sociodemographic attributes and risk behaviors were similar across all candidate PCAs, but risk behaviors of existing peer educators differed. Existing peer educators were more likely to engage in higher risk behavior such as receiving money for sex when compared to sociometrically selected peer changes agents. These existing peer educators were also more likely to exhibit leadership qualities within the overall network; they were, however, just as likely as other non-trained candidate peer change agents to report important HIV intravention behavior (encouraging condoms within their network). The importance of identifying bridges who may be able to diffuse innovation more effectively within high risk HIV networks is especially critical given recent efficacy data from novel HIV prevention interventions such as pre-exposure prophylaxis. Moreover, while existing peer educators were more likely to be leaders in our analysis, using peer educators with high risk behavior may have limited utility in enacting behavior change among sex worker peers or male clients in the network. PMID:24518188
Intelligent Software Agents: Sensor Integration and Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kulesz, James J; Lee, Ronald W
2013-01-01
Abstract In a post Macondo world the buzzwords are Integrity Management and Incident Response Management. The twin processes are not new but the opportunity to link the two is novel. Intelligent software agents can be used with sensor networks in distributed and centralized computing systems to enhance real-time monitoring of system integrity as well as manage the follow-on incident response to changing, and potentially hazardous, environmental conditions. The software components are embedded at the sensor network nodes in surveillance systems used for monitoring unusual events. When an event occurs, the software agents establish a new concept of operation at themore » sensing node, post the event status to a blackboard for software agents at other nodes to see , and then react quickly and efficiently to monitor the scale of the event. The technology addresses a current challenge in sensor networks that prevents a rapid and efficient response when a sensor measurement indicates that an event has occurred. By using intelligent software agents - which can be stationary or mobile, interact socially, and adapt to changing situations - the technology offers features that are particularly important when systems need to adapt to active circumstances. For example, when a release is detected, the local software agent collaborates with other agents at the node to exercise the appropriate operation, such as: targeted detection, increased detection frequency, decreased detection frequency for other non-alarming sensors, and determination of environmental conditions so that adjacent nodes can be informed that an event is occurring and when it will arrive. The software agents at the nodes can also post the data in a targeted manner, so that agents at other nodes and the command center can exercise appropriate operations to recalibrate the overall sensor network and associated intelligence systems. The paper describes the concepts and provides examples of real-world implementations including the Threat Detection and Analysis System (TDAS) at the International Port of Memphis and the Biological Warning and Incident Characterization System (BWIC) Environmental Monitoring (EM) Component. Technologies developed for these 24/7 operational systems have applications for improved real-time system integrity awareness as well as provide incident response (as needed) for production and field applications.« less
NASA Astrophysics Data System (ADS)
Görbil, Gökçe; Gelenbe, Erol
The simulation of critical infrastructures (CI) can involve the use of diverse domain specific simulators that run on geographically distant sites. These diverse simulators must then be coordinated to run concurrently in order to evaluate the performance of critical infrastructures which influence each other, especially in emergency or resource-critical situations. We therefore describe the design of an adaptive communication middleware that provides reliable and real-time one-to-one and group communications for federations of CI simulators over a wide-area network (WAN). The proposed middleware is composed of mobile agent-based peer-to-peer (P2P) overlays, called virtual networks (VNets), to enable resilient, adaptive and real-time communications over unreliable and dynamic physical networks (PNets). The autonomous software agents comprising the communication middleware monitor their performance and the underlying PNet, and dynamically adapt the P2P overlay and migrate over the PNet in order to optimize communications according to the requirements of the federation and the current conditions of the PNet. Reliable communications is provided via redundancy within the communication middleware and intelligent migration of agents over the PNet. The proposed middleware integrates security methods in order to protect the communication infrastructure against attacks and provide privacy and anonymity to the participants of the federation. Experiments with an initial version of the communication middleware over a real-life networking testbed show that promising improvements can be obtained for unicast and group communications via the agent migration capability of our middleware.
Social games in a social network.
Abramson, G; Kuperman, M
2001-03-01
We study an evolutionary version of the Prisoner's Dilemma game, played by agents placed in a small-world network. Agents are able to change their strategy, imitating that of the most successful neighbor. We observe that different topologies, ranging from regular lattices to random graphs, produce a variety of emergent behaviors. This is a contribution towards the study of social phenomena and transitions governed by the topology of the community.
Temporal Heterogeneity and the Value of Slowness in Robotic Systems
2015-11-01
DIMENSIONS OF HETEROGENEITY By now, we have become reasonably good at designing distributed control strategies for teams of networked agents in order...possible is the recent emergence of a relatively mature theory of how to coordinate control decisions across teams of networked agents. In fact...Loris, illustrated in Figure 2. Figure 2: Slow mammals that serve as bio-inspiration for SlowBot Behavior [Wikipedia] Top: Tree
A Multi-Agent System Architecture for Sensor Networks
Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo
2009-01-01
The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172
A multi-agent system architecture for sensor networks.
Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo
2009-01-01
The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.
Information specialist for a coming age (11)
NASA Astrophysics Data System (ADS)
Kamio, Tatsuo
In the business world 'CNN REVOLUTION' is prevailing. 'CNN REVOLUTION' means the information system organized mostly by the Computer and the Communication Network through which they can make a vital business judgment. They try to give customers better service, enjoy a higher share and be more competitive through the information system, which enables them to control various information inside their firm completely and use it most usefully. They are also trying to hard to make the information system effective enough to gather information outside their firm. In making use of information for business, it is vital to get 'intelligence' which analized and processed information and to expand information distribution inside their company freely. As a new field of activity information specialist are expected to take a more important role in developing how to get 'good intelligence' and making useful information accessible through the information system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pharhizgar, K.D.; Lunce, S.E.
1994-12-31
Development of knowledge-based technological acquisition techniques and customers` information profiles are known as assimilative integrated discovery systems (AIDS) in modern organizations. These systems have access through processing to both deep and broad domains of information in modern societies. Through these systems organizations and individuals can predict future trend probabilities and events concerning their customers. AIDSs are new techniques which produce new information which informants can use without the help of the knowledge sources because of the existence of highly sophisticated computerized networks. This paper has analyzed the danger and side effects of misuse of information through the illegal, unethical andmore » immoral access to the data-base in an integrated and assimilative information system as described above. Cognivistic mapping, pragmatistic informational design gathering, and holistic classifiable and distributive techniques are potentially abusive systems whose outputs can be easily misused by businesses when researching the firm`s customers.« less
Spreading of infection in a two species reaction-diffusion process in networks
NASA Astrophysics Data System (ADS)
Korosoglou, Paschalis; Kittas, Aristotelis; Argyrakis, Panos
2010-12-01
We study the dynamics of the infection of a two mobile species reaction from a single infected agent in a population of healthy agents. Historically, the main focus for infection propagation has been through spreading phenomena, where a random location of the system is initially infected and then propagates by successfully infecting its neighbor sites. Here both the infected and healthy agents are mobile, performing classical random walks. This may be a more realistic picture to such epidemiological models, such as the spread of a virus in communication networks of routers, where data travel in packets, the communication time of stations in ad hoc mobile networks, information spreading (such as rumor spreading) in social networks, etc. We monitor the density of healthy particles ρ(t) , which we find in all cases to be an exponential function in the long-time limit in two-dimensional and three-dimensional lattices and Erdős-Rényi (ER) and scale-free (SF) networks. We also investigate the scaling of the crossover time tc from short- to long-time exponential behavior, which we find to be a power law in lattices and ER networks. This crossover is shown to be absent in SF networks, where we reveal the role of the connectivity of the network in the infection process. We compare this behavior to ER networks and lattices and highlight the significance of various connectivity patterns, as well as the important differences of this process in the various underlying geometries, revealing a more complex behavior of ρ(t) .
Song, Yujiang; Shelnutt, John A.
2012-11-06
A metallic nanowire network synthesized using chemical reduction of a metal ion source by a reducing agent in the presence of a soft template comprising a tubular inverse micellar network. The network of interconnected polycrystalline nanowires has a very high surface-area/volume ratio, which makes it highly suitable for use in catalytic applications.
The dynamics of financial stability in complex networks
NASA Astrophysics Data System (ADS)
da Cruz, J. P.; Lind, P. G.
2012-08-01
We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each other to exchange `economic energy', forming a network of trades. When the capital level of one economic agent drops below a minimum, the economic agent becomes insolvent. The insolvency of one single economic agent affects the economic energy of all its neighbours which thus become susceptible to insolvency, being able to trigger a chain of insolvencies (avalanche). We show that the distribution of avalanche sizes follows a power-law whose exponent depends on the minimum capital level. Furthermore, we present evidence that under an increase in the minimum capital level, large crashes will be avoided only if one assumes that agents will accept a drop in business levels, while keeping their trading attitudes and policies unchanged. The alternative assumption, that agents will try to restore their business levels, may lead to the unexpected consequence that large crises occur with higher probability.
Medical service provider networks.
Mougeot, Michel; Naegelen, Florence
2018-05-17
In many countries, health insurers or health plans choose to contract either with any willing providers or with preferred providers. We compare these mechanisms when two medical services are imperfect substitutes in demand and are supplied by two different firms. In both cases, the reimbursement is higher when patients select the in-network provider(s). We show that these mechanisms yield lower prices, lower providers' and insurer's profits, and lower expense than in the uniform-reimbursement case. Whatever the degree of product differentiation, a not-for-profit insurer should prefer selective contracting and select a reimbursement such that the out-of-pocket expense is null. Although all providers join the network under any-willing-provider contracting in the absence of third-party payment, an asymmetric equilibrium may exist when this billing arrangement is implemented. Copyright © 2018 John Wiley & Sons, Ltd.
Boolean network representation of contagion dynamics during a financial crisis
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2015-01-01
This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.
Controllability of social networks and the strategic use of random information.
Cremonini, Marco; Casamassima, Francesca
2017-01-01
This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network and considers two well-known strategies for influencing social contexts: One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad hoc metrics which are defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills. These findings support our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable.
The challenge of contracting for technological information.
Zeckhauser, R
1996-11-12
Contracting to provide technological information (TI) is a significant challenge. TI is an unusual commodity in five ways. (i) TI is difficult to count and value; conventional indicators, such as patients and citations, hardly indicate value. TI is often sold at different prices to different parties. (ii) To value TI, it may be necessary to "give away the secret." This danger, despite nondisclosure agreements, inhibits efforts to market TI. (iii) To prove its value, TI is often bundled into complete products, such as a computer chip or pharmaceutical product. Efficient exchange, by contrast, would involve merely the raw information. (iv) Sellers' superior knowledge about TI's value make buyers wary of overpaying. (v) Inefficient contracts are often designed to secure rents from TI. For example, licensing agreements charge more than marginal cost. These contracting difficulties affect the way TI is produced, encouraging self-reliance. This should be an advantage to large firms. However, small research and development firms spend more per employee than large firms, and nonprofit universities are major producers. Networks of organizational relationships, particularly between universities and industry, are critical in transmitting TI. Implicit barter-money for guidance-is common. Property rights for TI are hard to establish. Patents, quite suitable for better mousetraps, are inadequate for an era when we design better mice. Much TI is not patented, and what is patented sets fuzzy demarcations. New organizational forms are a promising approach to contracting difficulties for TI. Webs of relationships, formal and informal, involving universities, start-up firms, corporate giants, and venture capitalists play a major role in facilitating the production and spread of TI.
The challenge of contracting for technological information
Zeckhauser, Richard
1996-01-01
Contracting to provide technological information (TI) is a significant challenge. TI is an unusual commodity in five ways. (i) TI is difficult to count and value; conventional indicators, such as patents and citations, hardly indicate value. TI is often sold at different prices to different parties. (ii) To value TI, it may be necessary to “give away the secret.” This danger, despite nondisclosure agreements, inhibits efforts to market TI. (iii) To prove its value, TI is often bundled into complete products, such as a computer chip or pharmaceutical product. Efficient exchange, by contrast, would involve merely the raw information. (iv) Sellers’ superior knowledge about TI’s value make buyers wary of overpaying. (v) Inefficient contracts are often designed to secure rents from TI. For example, licensing agreements charge more than marginal cost. These contracting difficulties affect the way TI is produced, encouraging self-reliance. This should be an advantage to large firms. However, small research and development firms spend more per employee than large firms, and nonprofit universities are major producers. Networks of organizational relationships, particularly between universities and industry, are critical in transmitting TI. Implicit barter—money for guidance—is common. Property rights for TI are hard to establish. Patents, quite suitable for better mousetraps, are inadequate for an era when we design better mice. Much TI is not patented, and what is patented sets fuzzy demarcations. New organizational forms are a promising approach to contracting difficulties for TI. Webs of relationships, formal and informal, involving universities, start-up firms, corporate giants, and venture capitalists play a major role in facilitating the production and spread of TI. PMID:8917488
Information flow in a network of dispersed signalers-receivers
NASA Astrophysics Data System (ADS)
Halupka, Konrad
2017-11-01
I consider a stochastic model of multi-agent communication in regular network. The model describes how dispersed animals exchange information. Each agent can initiate and transfer the signal to its nearest neighbors, who may pass it farther. For an external observer of busy networks, signaling activity may appear random, even though information flow actually thrives. Only when signal initiation and transfer are at low levels do spatiotemporal autocorrelations emerge as clumping signaling activity in space and pink noise time series. Under such conditions, the costs of signaling are moderate, but the signaler can reach a large audience. I propose that real-world networks of dispersed signalers-receivers may self-organize into this state and the flow of information maintains their integrity.
A clustering algorithm for determining community structure in complex networks
NASA Astrophysics Data System (ADS)
Jin, Hong; Yu, Wei; Li, ShiJun
2018-02-01
Clustering algorithms are attractive for the task of community detection in complex networks. DENCLUE is a representative density based clustering algorithm which has a firm mathematical basis and good clustering properties allowing for arbitrarily shaped clusters in high dimensional datasets. However, this method cannot be directly applied to community discovering due to its inability to deal with network data. Moreover, it requires a careful selection of the density parameter and the noise threshold. To solve these issues, a new community detection method is proposed in this paper. First, we use a spectral analysis technique to map the network data into a low dimensional Euclidean Space which can preserve node structural characteristics. Then, DENCLUE is applied to detect the communities in the network. A mathematical method named Sheather-Jones plug-in is chosen to select the density parameter which can describe the intrinsic clustering structure accurately. Moreover, every node on the network is meaningful so there were no noise nodes as a result the noise threshold can be ignored. We test our algorithm on both benchmark and real-life networks, and the results demonstrate the effectiveness of our algorithm over other popularity density based clustering algorithms adopted to community detection.
Control of Synchronization Regimes in Networks of Mobile Interacting Agents
NASA Astrophysics Data System (ADS)
Perez-Diaz, Fernando; Zillmer, Ruediger; Groß, Roderich
2017-05-01
We investigate synchronization in a population of mobile pulse-coupled agents with a view towards implementations in swarm-robotics systems and mobile sensor networks. Previous theoretical approaches dealt with range and nearest-neighbor interactions. In the latter case, a synchronization-hindering regime for intermediate agent mobility is found. We investigate the robustness of this intermediate regime under practical scenarios. We show that synchronization in the intermediate regime can be predicted by means of a suitable metric of the phase response curve. Furthermore, we study more-realistic K -nearest-neighbor and cone-of-vision interactions, showing that it is possible to control the extent of the synchronization-hindering region by appropriately tuning the size of the neighborhood. To assess the effect of noise, we analyze the propagation of perturbations over the network and draw an analogy between the response in the hindering regime and stable chaos. Our findings reveal the conditions for the control of clock or activity synchronization of agents with intermediate mobility. In addition, the emergence of the intermediate regime is validated experimentally using a swarm of physical robots interacting with cone-of-vision interactions.
Damage spreading and opinion dynamics on scale-free networks
NASA Astrophysics Data System (ADS)
Fortunato, Santo
2005-03-01
We study damage spreading among the opinions of a system of agents, subjected to the dynamics of the Krause-Hegselmann consensus model. The damage consists in a sharp change of the opinion of one or more agents in the initial random opinion configuration, supposedly due to some external factors and/or events. This may help to understand for instance under which conditions special shocking events or targeted propaganda are able to influence the results of elections. For agents lying on the nodes of a Barabási-Albert network, there is a damage spreading transition at a low value εd of the confidence bound parameter. Interestingly, we find as well that there is some critical value εs above which the initial perturbation manages to propagate to all other agents.
Re-Examining of Moffitt’s Theory of Delinquency through Agent Based Modeling
Leaw, Jia Ning; Ang, Rebecca P.; Huan, Vivien S.; Chan, Wei Teng; Cheong, Siew Ann
2015-01-01
Moffitt’s theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome. PMID:26062022
ERIC Educational Resources Information Center
Cerf, M.; Guillot, M. N.; Olry, P.
2011-01-01
How do change agents deal with the diversity of farmers' attitudes towards the future of agriculture? How do they themselves cope with change and understand their role as change agents? We chose a comprehensive, action-training approach to answer such questions and worked with agents belonging to two different extension networks. The agents…