Sample records for distributed artificial intelligence

  1. A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems

    DTIC Science & Technology

    1990-11-01

    Intelligence Systems," in Distributed Artifcial Intelligence , vol. II, L. Gasser and M. Huhns (eds), Pitman, London, 1989, pp. 413-430. Shaw, M. Harrow, B...IDTIC FILE COPY A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems N Michael I. Shaw...SUBTITLE 5. FUNDING NUMBERS A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems 6

  2. Actors: A Model of Concurrent Computation in Distributed Systems.

    DTIC Science & Technology

    1985-06-01

    Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SY𔃿TEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI

  3. Coordination in Distributed Intelligent Systems Applications

    DTIC Science & Technology

    2009-12-13

    working in the area of Distributed Artificial Intelligence (DAI) unanimously endorses the idea that coordination - a fundamental paradigm - represents a...using the distributed artificial intelligence paradigm. Section 4 discusses the healthcare applications. On the other hand, Section 5 describes...coordination mechanisms should be used is in the control of swarms of UA Vs (unmanned aerial vehicles). The UAVs are considered in this case as highly mobile

  4. Challenges facing the distribution of an artificial-intelligence-based system for nursing.

    PubMed

    Evans, S

    1985-04-01

    The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

  5. Using Crowdsourced Geospatial Data to Aid in Nuclear Proliferation Monitoring

    DTIC Science & Technology

    2016-12-01

    M. Stephens, and Ronald D. Bonnell, “DAI for Document Retrieval: The MINDS Project,” in Distributed Artificial Intelligence , ed. Michael N. Huhns...Ronald D. Bonnell. “DAI for Document Retrieval: The MINDS Project,” In Distributed Artificial Intelligence , edited by Michael N. Huhns, 249–283...was for the director of National Intelligence to explore ways that crowdsourced geospatial imagery technologies could aid existing governmental

  6. Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

    ERIC Educational Resources Information Center

    Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

    2014-01-01

    In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

  7. The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

    PubMed

    Collado-Mesa, Fernando; Alvarez, Edilberto; Arheart, Kris

    2018-02-21

    Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey was conducted among trainees and attending radiologists at a single residency program. An anonymous questionnaire was distributed. Comparisons of categorical data between groups (trainees and attending radiologists) were made using Pearson χ 2 analysis or an exact analysis when required. Comparisons were made using the Wilcoxon rank sum test when the data were not normally distributed. An α level of 0.05 was used. The overall response rate was 66% (69 of 104). Thirty-six percent of participants (n = 25) reported not having read a scientific medical article on the topic of artificial intelligence during the past 12 months. Twenty-nine percent of respondents (n = 12) reported using artificial intelligence tools during their daily work. Trainees were more likely to express doubts on whether they would have pursued diagnostic radiology as a career had they known of the potential impact artificial intelligence is predicted to have on the specialty (P = .0254) and were also more likely to plan to learn about the topic (P = .0401). Radiologists lack exposure to current scientific medical articles on artificial intelligence. Trainees are concerned by the implications artificial intelligence may have on their jobs and desire to learn about the topic. There is a need to develop educational resources to help radiologists assume an active role in guiding and facilitating the development and implementation of artificial intelligence tools in diagnostic radiology. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  8. AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search

    DTIC Science & Technology

    1976-07-01

    Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Len-t APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED (A...570 AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Lenat ABSTRACT A program, called "AM", is...While AM’s " approach " to empirical research may be used in other scientific domains, the main limitation (reliance on hindsight) will probably recur

  9. Application of artificial intelligence to the management of urological cancer.

    PubMed

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  10. Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

    DTIC Science & Technology

    1991-06-01

    Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

  11. Repairing Learned Knowledge Using Experience

    DTIC Science & Technology

    1990-05-01

    34 Artifcial Intelligence Journal, vol. 19, no. 3. Winston, Patrick Henry (1984], Artificial Intelligence , Second Edition, Addison-Wesley. Analogical...process speeds up future problem solving, but the scope of the learni ng- augmented theory remains unchanged. In con- (continued on back) PD D J7 1473...Distribution/ Avaiability Codes Avail and/or .Dist Special MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 1231

  12. The use of artificially intelligent agents with bounded rationality in the study of economic markets

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

    Rajan, V.; Slagle, J.R.

    The concepts of {open_quote}knowledge{close_quote} and {open_quote}rationality{close_quote} are of central importance to fields of science that are interested in human behavior and learning, such as artificial intelligence, economics, and psychology. The similarity between artificial intelligence and economics - both are concerned with intelligent thought, rational behavior, and the use and acquisition of knowledge - has led to the use of economic models as a paradigm for solving problems in distributed artificial intelligence (DAI) and multi agent systems (MAS). What we propose is the opposite; the use of artificial intelligence in the study of economic markets. Over the centuries various theories ofmore » market behavior have been advanced. The prevailing theory holds that an asset`s current price converges to the risk adjusted value of the rationally expected dividend stream. While this rational expectations model holds in equilibrium or near-equilibrium conditions, it does not sufficiently explain conditions of market disequilibrium. An example of market disequilibrium is the phenomenon of a speculative bubble. We present an example of using artificially intelligent agents with bounded rationality in the study of speculative bubbles.« less

  13. Distribution Planning: An Integration of Constraint Satisfaction & Heuristic Search Techniques

    DTIC Science & Technology

    1990-01-01

    Proceedings of the Symposium on Aritificial Intelligence in ~~litary Logistics, Arlington, VA: American Defense Preparedness Assoc. pp. 177-182...dynamic changes, too many variables, and lack pf planning time. The Human Engineeri n ~ Laboratory (HEL) is developing artificial intelligence (AI...first attempt. The field of artificial intelligence includes a variety of knowledge-based approaches. Most widely known are Expert Systems, that are

  14. Exodus - Distributed artificial intelligence for Shuttle firing rooms

    NASA Technical Reports Server (NTRS)

    Heard, Astrid E.

    1990-01-01

    This paper describes the Expert System for Operations Distributed Users (EXODUS), a knowledge-based artificial intelligence system developed for the four Firing Rooms at the Kennedy Space Center. EXODUS is used by the Shuttle engineers and test conductors to monitor and control the sequence of tasks required for processing and launching Shuttle vehicles. In this paper, attention is given to the goals and the design of EXODUS, the operational requirements, and the extensibility of the technology.

  15. An overview of the artificial intelligence and expert systems component of RICIS

    NASA Technical Reports Server (NTRS)

    Feagin, Terry

    1987-01-01

    Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.

  16. Northeast Artificial Intelligence Consortium Annual Report. Volume 6. 1988 Building an Intelligent Assistant: The Acquisition, Integration, and Maintenance of Complex Distributed Tasks

    DTIC Science & Technology

    1989-10-01

    of.ezpertiae Seymour. Wright (or artificisi. intelligence distributed. ai planning robo tics computer.vsion))." Implementation: (replace-values-in-constraint...by mechanical partners or advisors that customize the system’s response to the idiosyncrasies of the student. This paper describes the initial

  17. A system for intelligent teleoperation research

    NASA Technical Reports Server (NTRS)

    Orlando, N. E.

    1983-01-01

    The Automation Technology Branch of NASA Langley Research Center is developing a research capability in the field of artificial intelligence, particularly as applicable in teleoperator/robotics development for remote space operations. As a testbed for experimentation in these areas, a system concept has been developed and is being implemented. This system termed DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), interfaces the key processes of perception, reasoning, and manipulation by linking hardware sensors and manipulators to a modular artificial intelligence (AI) software system in a hierarchical control structure. Verification experiments have been performed: one experiment used a blocksworld database and planner embedded in the DAISIE system to intelligently manipulate a simple physical environment; the other experiment implemented a joint-space collision avoidance algorithm. Continued system development is planned.

  18. Mission Profiles and Evidential Reasoning for Estimating Information Relevancy in Multi-Agent Supervisory Control Applications

    DTIC Science & Technology

    2010-06-01

    artificial agents, their limited scope and singular purpose lead us to believe that human-machine trust will be very portable. That is, if one operator... Artificial Intelligence Review 2(2), 1988. [E88] M.R. Endsley. Situation awareness global assessment technique (SAGAT). In Proceedings of the National...1995. [F98] J. Ferber, Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence, Addison- Wesley, 1998. [NP01] I. Niles and A

  19. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  20. Application Of Artificial Intelligence To Wind Tunnels

    NASA Technical Reports Server (NTRS)

    Lo, Ching F.; Steinle, Frank W., Jr.

    1989-01-01

    Report discusses potential use of artificial-intelligence systems to manage wind-tunnel test facilities at Ames Research Center. One of goals of program to obtain experimental data of better quality and otherwise generally increase productivity of facilities. Another goal to increase efficiency and expertise of current personnel and to retain expertise of former personnel. Third goal to increase effectiveness of management through more efficient use of accumulated data. System used to improve schedules of operation and maintenance of tunnels and other equipment, assignment of personnel, distribution of electrical power, and analysis of costs and productivity. Several commercial artificial-intelligence computer programs discussed as possible candidates for use.

  1. Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

    ERIC Educational Resources Information Center

    Solomos, Konstantinos; Avouris, Nikolaos

    1999-01-01

    Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

  2. Using Artificial Physics to Control Agents

    DTIC Science & Technology

    1999-11-01

    unlimited 13. SUPPLEMENTARY NOTES IEEE International Conference on Information, Intelligence, and Systems, Oct 31 -Nov 3,1999. Bethesda, MD 14. ABSTRACT...distributed control can also perform distributed computation. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same...1995. [9] H. Pattee. Artificial life needs a real epistemology. In Moran, Moreno, Merelo, and Chacon , editors, Advances in Artificial Life, pages

  3. A development framework for artificial intelligence based distributed operations support systems

    NASA Technical Reports Server (NTRS)

    Adler, Richard M.; Cottman, Bruce H.

    1990-01-01

    Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

  4. The 1991 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1991-01-01

    The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.

  5. A development framework for distributed artificial intelligence

    NASA Technical Reports Server (NTRS)

    Adler, Richard M.; Cottman, Bruce H.

    1989-01-01

    The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

  6. The Brain as a Distributed Intelligent Processing System: An EEG Study

    PubMed Central

    da Rocha, Armando Freitas; Rocha, Fábio Theoto; Massad, Eduardo

    2011-01-01

    Background Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion The present results support these claims and the neural efficiency hypothesis. PMID:21423657

  7. Artificial intelligence and space power systems automation

    NASA Technical Reports Server (NTRS)

    Weeks, David J.

    1987-01-01

    Various applications of artificial intelligence to space electrical power systems are discussed. An overview is given of completed, on-going, and planned knowledge-based system activities. These applications include the Nickel-Cadmium Battery Expert System (NICBES) (the expert system interfaced with the Hubble Space Telescope electrical power system test bed); the early work with the Space Station Experiment Scheduler (SSES); the three expert systems under development in the space station advanced development effort in the core module power management and distribution system test bed; planned cooperation of expert systems in the Core Module Power Management and Distribution (CM/PMAD) system breadboard with expert systems for the space station at other research centers; and the intelligent data reduction expert system under development.

  8. Artificial intelligence in a mission operations and satellite test environment

    NASA Technical Reports Server (NTRS)

    Busse, Carl

    1988-01-01

    A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.

  9. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    NASA Technical Reports Server (NTRS)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

  10. Model architecture of intelligent data mining oriented urban transportation information

    NASA Astrophysics Data System (ADS)

    Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

    2007-06-01

    Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

  11. The application and development of artificial intelligence in smart clothing

    NASA Astrophysics Data System (ADS)

    Wei, Xiong

    2018-03-01

    This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

  12. Multi-Agent Information Classification Using Dynamic Acquaintance Lists.

    ERIC Educational Resources Information Center

    Mukhopadhyay, Snehasis; Peng, Shengquan; Raje, Rajeev; Palakal, Mathew; Mostafa, Javed

    2003-01-01

    Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

  13. Parallel Logic Programming Architecture

    DTIC Science & Technology

    1990-04-01

    Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during

  14. A multi-assets artificial stock market with zero-intelligence traders

    NASA Astrophysics Data System (ADS)

    Ponta, L.; Raberto, M.; Cincotti, S.

    2011-01-01

    In this paper, a multi-assets artificial financial market populated by zero-intelligence traders with finite financial resources is presented. The market is characterized by different types of stocks representing firms operating in different sectors of the economy. Zero-intelligence traders follow a random allocation strategy which is constrained by finite resources, past market volatility and allocation universe. Within this framework, stock price processes exhibit volatility clustering, fat-tailed distribution of returns and reversion to the mean. Moreover, the cross-correlations between returns of different stocks are studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. It is worth noting that business sectors have been recovered in our framework without dividends as only consequence of random restrictions on the allocation universe of zero-intelligence traders. Furthermore, in the presence of dividend-paying stocks and in the case of cash inflow added to the market, the artificial stock market points out the same structural results obtained in the simulation without dividends. These results suggest a significative structural influence on statistical properties of multi-assets stock market.

  15. Northeast Artificial Intelligence Consortium (NAIC). Volume 4. Distributed Artificial Intelligence for Communications Network Management

    DTIC Science & Technology

    1990-12-01

    subject to resource constraints. Mul- tista~ze negotiation has been developed as a means by which an agent can acquire ,em 0ugh additional knowledge to...complete knowledge often expands the search space without providing a compensatiN means for focusing the search. In a multi-agent system with each...These relationships have strengthened our abilities to conduct meaningful research and to assist the transfer of technolog frni th, 81 university

  16. Shake, Rattle and Roles: Lessons from Experimental Earthquake Engineering for Incorporating Remote Users in Large-Scale E-Science Experiments

    DTIC Science & Technology

    2007-01-01

    Mechanical Turk: Artificial Artificial Intelligence . Retrieved May 15, 2006 from http://www.mturk.com/ mturk/welcome Atkins, D. E., Droegemeier, K. K...Turk (Amazon, 2006) site goes beyond volunteers and pays people to do Human Intelligence Tasks, those that are difficult for computers but relatively...geographically distributed scientific collaboration, and the use of videogame technology for training. Address: U.S. Army Research Institute, 2511 Jefferson

  17. Learning Unknown Event Models

    DTIC Science & Technology

    2014-07-01

    Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

  18. A Collection of Technical Studies Completed for the Computer-Aided Acquisition and Logistic Support (CALS) Program Fiscal Year 1988. Volume 1. Text, Security and Data Management

    DTIC Science & Technology

    1991-03-01

    management methodologies claim to be "expert systems" with security intelligence built into them to I derive a body of both facts and speculative data ... Data Administration considerations . III -21 IV. ARTIFICIAL INTELLIGENCE . .. .. .. . .. IV - 1 A. Description of Technologies . . . . . .. IV - 1 1...as intelligent gateways, wide area networks, and distributed databases for the distribution of logistics products. The integrity of CALS data and the

  19. Robotics with Natural Language Comprehension and Learning Abilities.

    DTIC Science & Technology

    1985-01-01

    Artificial intellignece implications for knowledge retrivedO. Accession For NTIGRA&I DTIC TAB Unannounced 0 Justifioation *5**.By I Distribution...through understanding and generalizing plans", "An approach to learning from observation", and " Artificial intelligence implications for knowledge

  20. Multi-Agent Framework for Virtual Learning Spaces.

    ERIC Educational Resources Information Center

    Sheremetov, Leonid; Nunez, Gustavo

    1999-01-01

    Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

  1. Programming model for distributed intelligent systems

    NASA Technical Reports Server (NTRS)

    Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

    1988-01-01

    A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

  2. Bug Distribution and Statistical Pattern Classification.

    ERIC Educational Resources Information Center

    Tatsuoka, Kikumi K.; Tatsuoka, Maurice M.

    1987-01-01

    The rule space model permits measurement of cognitive skill acquisition and error diagnosis. Further discussion introduces Bayesian hypothesis testing and bug distribution. An illustration involves an artificial intelligence approach to testing fractions and arithmetic. (Author/GDC)

  3. Use of artificial intelligence to analyze clinical database reduces workload on surgical house staff.

    PubMed

    Grossi, E A; Steinberg, B M; LeBoutillier, M; Coppa, G F; Roses, D F

    1994-08-01

    The current quantity and diversity of hospital clinical, laboratory, and pharmacy records have resulted in a glut of information, which can be overwhelming to house staff. This study was performed to measure the impact of artificial intelligence analysis of such data on the junior surgical house staff's workload, time for direct patient care, and quality of life. A personal computer was interfaced with the hospital computerized patient data system. Artificial intelligence algorithms were applied to retrieve and condense laboratory values, microbiology reports, and medication orders. Unusual laboratory tests were reported without artificial intelligence filtering. A survey of 23 junior house staff showed a requirement for a total of 30.75 man-hours per day, an average of 184.5 minutes per service twice a day for five surgical services each with an average of 40.7 patients, to manually produce a report in contrast to a total of 3.4 man-hours, an average of 20.5 minutes on the same basis (88.9% reduction, p < 0.001), to computer generate and distribute a similarly useful report. Two thirds of the residents reported an increased ability to perform patient care. Current medical practice has created an explosion of information, which is a burden for surgical house staff. Artificial intelligence preprocessing of the hospital database information focuses attention, eliminates superfluous data, and significantly reduces surgical house staff clerical work, allowing more time for education, research, and patient care.

  4. Northeast Artificial Intelligence Consortium annual report. Volume 2. 1988. Discussing, using, and recognizing plans (NLP). Interim report, January-December 1988

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

    Shapiro, S.C.; Woolf, B.

    The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and the Office of Scientific Research. Its purpose is to conduct pertinent research in artificial intelligence and to perform activities ancillary to this research. This report describes progress that has been made in the fourth year of the existence of the NAIC on the technical research tasks undertaken at the member universities. The topics covered in general are: versatile expert system for equipment maintenance, distributed AI for communications system control, automatic photointerpretation, time-oriented problem solving, speech understanding systems, knowledge base maintenance, hardwaremore » architectures for very large systems, knowledge-based reasoning and planning, and a knowledge acquisition, assistance, and explanation system. The specific topic for this volume is the recognition of plans expressed in natural language, followed by their discussion and use.« less

  5. An Innovative Multi-Agent Search-and-Rescue Path Planning Approach

    DTIC Science & Technology

    2015-03-09

    search problems from search theory and artificial intelligence /distributed robotic control, and pursuit-evasion problem perspectives may be found in...Dissanayake, “Probabilistic search for a moving target in an indoor environment”, In Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems, 2006, pp...3393-3398. [7] H. Lau, and G. Dissanayake, “Optimal search for multiple targets in a built environment”, In Proc. IEEE/RSJ Int. Conf. Intelligent

  6. Artificial Intelligence and Information Retrieval.

    ERIC Educational Resources Information Center

    Teodorescu, Ioana

    1987-01-01

    Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)

  7. Towards Distributed Intelligence: A High Level Definition

    DTIC Science & Technology

    2004-12-01

    Some of the first research in multi-robot systems came in the foraging /sorting area by Parker [77] and Beckers [9] and was likely fueled by the bio...chapter 24, pages 28–39. Artificial Intelligence at MIT. The MIT Press, 1989. 15. R.A. Brooks. Robotic Science, chapter 11, The Whole Iguana , pages 432

  8. First CLIPS Conference Proceedings, volume 2

    NASA Technical Reports Server (NTRS)

    1990-01-01

    The topics of volume 2 of First CLIPS Conference are associated with following applications: quality control; intelligent data bases and networks; Space Station Freedom; Space Shuttle and satellite; user interface; artificial neural systems and fuzzy logic; parallel and distributed processing; enchancements to CLIPS; aerospace; simulation and defense; advisory systems and tutors; and intelligent control.

  9. CREATIVE COMPUTATION.

    DTIC Science & Technology

    ARTIFICIAL INTELLIGENCE , RECURSIVE FUNCTIONS), (*RECURSIVE FUNCTIONS, ARTIFICIAL INTELLIGENCE ), (*MATHEMATICAL LOGIC, ARTIFICIAL INTELLIGENCE ), METAMATHEMATICS, AUTOMATA, NUMBER THEORY, INFORMATION THEORY, COMBINATORIAL ANALYSIS

  10. Artificial Intelligence and Its Importance in Education.

    ERIC Educational Resources Information Center

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  11. Northeast Artificial Intelligence Consortium (NAIC) Review of Technical Tasks. Volume 2, Part 2.

    DTIC Science & Technology

    1987-07-01

    A-A19 774 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUN (MIC) 1/5 YVIEN OF TEOICR. T.. (U) NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM SYRACUSE MY J...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM (NAIC) *p,* ~ Review of Technical Tasks ,.. 12 PERSONAL AUTHOR(S) (See reverse) . P VI J.F. Allen, P.B. Berra...See reverse) /" I ABSTRACT (Coninue on ’.wrse if necessary and identify by block number) % .. *. -. ’ The Northeast Artificial Intelligence Consortium

  12. Artificial intelligence in medicine.

    PubMed Central

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  13. Artificial intelligence in medicine.

    PubMed

    Ramesh, A N; Kambhampati, C; Monson, J R T; Drew, P J

    2004-09-01

    Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting.

  14. Artificial intelligence support for scientific model-building

    NASA Technical Reports Server (NTRS)

    Keller, Richard M.

    1992-01-01

    Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

  15. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  16. Estimation of urban runoff and water quality using remote sensing and artificial intelligence.

    PubMed

    Ha, S R; Park, S Y; Park, D H

    2003-01-01

    Water quality and quantity of runoff are strongly dependent on the landuse and landcover (LULC) criteria. In this study, we developed a more improved parameter estimation procedure for the environmental model using remote sensing (RS) and artificial intelligence (AI) techniques. Landsat TM multi-band (7bands) and Korea Multi-Purpose Satellite (KOMPSAT) panchromatic data were selected for input data processing. We employed two kinds of artificial intelligence techniques, RBF-NN (radial-basis-function neural network) and ANN (artificial neural network), to classify LULC of the study area. A bootstrap resampling method, a statistical technique, was employed to generate the confidence intervals and distribution of the unit load. SWMM was used to simulate the urban runoff and water quality and applied to the study watershed. The condition of urban flow and non-point contaminations was simulated with rainfall-runoff and measured water quality data. The estimated total runoff, peak time, and pollutant generation varied considerably according to the classification accuracy and percentile unit load applied. The proposed procedure would efficiently be applied to water quality and runoff simulation in a rapidly changing urban area.

  17. Proceedings of the Association for Computing Machinery Special Interest Group for Ada Artificial Intelligence Working Group, 1992 Summer Workshop Held in Seattle, Washington on June 24-27, 1992

    DTIC Science & Technology

    1993-06-01

    June 1993 Special Interest Group for Ada Artificial Intelligence Working Group 1992 Summer Workshop Janet Faye Johns Ac- i cr N 7 Dilt S ." Contract ...Sponsor %/A Contract No. N/A Project No. G30D [- t Dept. G033 Approved for public release. distribution unlimited. MITRE Bedford, Massachusetts ABSTRACT...FAX) George (Rick) Wilbur Boeing Computer Services Box 24346, Mailstop 9H-84 Seattle, WA 98124 206-394-3055 (phone) 206-394-3064 (FAX) Mik Yen

  18. Extensions to the Parallel Real-Time Artificial Intelligence System (PRAIS) for fault-tolerant heterogeneous cycle-stealing reasoning

    NASA Technical Reports Server (NTRS)

    Goldstein, David

    1991-01-01

    Extensions to an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS) are discussed. PRAIS strives for transparently parallelizing production (rule-based) systems, even under real-time constraints. PRAIS accomplished these goals (presented at the first annual C Language Integrated Production System (CLIPS) conference) by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors. Results using the original PRAIS architecture over a network of Sun 3's, Sun 4's and VAX's are presented. Mechanisms using the producer-consumer model to extend the architecture for fault-tolerance and distributed truth maintenance initiation are also discussed.

  19. Artificial Intelligence Project

    DTIC Science & Technology

    1990-01-01

    Artifcial Intelligence Project at The University of Texas at Austin, University of Texas at Austin, Artificial Intelligence Laboratory AITR84-01. Novak...Texas at Austin, Artificial Intelligence Laboratory A187-52, April 1987. Novak, G. "GLISP: A Lisp-Based Programming System with Data Abstraction...of Texas at Austin, Artificial Intelligence Laboratory AITR85-14.) Rim, Hae-Chang, and Simmons, R. F. "Extracting Data Base Knowledge from Medical

  20. An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusions

    DTIC Science & Technology

    2007-03-01

    Intelligence AIS Artificial Immune System ANN Artificial Neural Networks API Application Programming Interface BFS Breadth-First Search BIS Biological...problem domain is too large for only one algorithm’s application . It ranges from network - based sniffer systems, responsible for Enterprise-wide coverage...options to network administrators in choosing detectors to employ in future ID applications . Objectives Our hypothesis validity is based on a set

  1. Artificial Intelligence and Vocational Education: An Impending Confluence.

    ERIC Educational Resources Information Center

    Roth, Gene L.; McEwing, Richard A.

    1986-01-01

    Reports on the relatively new field of artificial intelligence and its relationship to vocational education. Compares human intelligence with artificial intelligence. Discusses expert systems, natural language technology, and current trends. Lists potential applications for vocational education. (CH)

  2. Resource-constrained Data Collection and Fusion for Identifying Weak Distributed Patterns in Networks

    DTIC Science & Technology

    2013-10-15

    statistic,” in Artifical Intelligence and Statistics (AISTATS), 2013. [6] ——, “Detecting activity in graphs via the Graph Ellipsoid Scan Statistic... Artifical Intelligence and Statistics (AISTATS), 2013. [8] ——, “Near-optimal anomaly detection in graphs using Lovász Extended Scan Statistic,” in Neural...networks,” in Artificial Intelligence and Statistics (AISTATS), 2010. 11 [11] D. Aldous, “The random walk construction of uniform spanning trees and

  3. Web Intelligence and Artificial Intelligence in Education

    ERIC Educational Resources Information Center

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  4. Northeast Artificial Intelligence Consortium Annual Report. Volume 2. 1988 Discussing, Using, and Recognizing Plans (NLP)

    DTIC Science & Technology

    1989-10-01

    Encontro Portugues de Inteligencia Artificial (EPIA), Oporto, Portugal, September 1985. [15] N. J. Nilsson. Principles Of Artificial Intelligence. Tioga...FI1 F COPY () RADC-TR-89-259, Vol II (of twelve) Interim Report October 1969 AD-A218 154 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL...7a. NAME OF MONITORING ORGANIZATION Northeast Artificial Of p0ilcabe) Intelligence Consortium (NAIC) Rome_____ Air___ Development____Center

  5. Distributions of Cognates in Europe as Based on Levenshtein Distance

    ERIC Educational Resources Information Center

    Schepens, Job; Dijkstra, Ton; Grootjen, Franc

    2012-01-01

    Researchers on bilingual processing can benefit from computational tools developed in artificial intelligence. We show that a normalized Levenshtein distance function can efficiently and reliably simulate bilingual orthographic similarity ratings. Orthographic similarity distributions of cognates and non-cognates were identified across pairs of…

  6. Intelligence: Real or artificial?

    PubMed Central

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

  7. Emerging trends in geospatial artificial intelligence (geoAI): potential applications for environmental epidemiology.

    PubMed

    VoPham, Trang; Hart, Jaime E; Laden, Francine; Chiang, Yao-Yi

    2018-04-17

    Geospatial artificial intelligence (geoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning (e.g., deep learning), data mining, and high-performance computing to extract knowledge from spatial big data. In environmental epidemiology, exposure modeling is a commonly used approach to conduct exposure assessment to determine the distribution of exposures in study populations. geoAI technologies provide important advantages for exposure modeling in environmental epidemiology, including the ability to incorporate large amounts of big spatial and temporal data in a variety of formats; computational efficiency; flexibility in algorithms and workflows to accommodate relevant characteristics of spatial (environmental) processes including spatial nonstationarity; and scalability to model other environmental exposures across different geographic areas. The objectives of this commentary are to provide an overview of key concepts surrounding the evolving and interdisciplinary field of geoAI including spatial data science, machine learning, deep learning, and data mining; recent geoAI applications in research; and potential future directions for geoAI in environmental epidemiology.

  8. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Thornburg, David D.

    1986-01-01

    Overview of the artificial intelligence (AI) field provides a definition; discusses past research and areas of future research; describes the design, functions, and capabilities of expert systems and the "Turing Test" for machine intelligence; and lists additional sources for information on artificial intelligence. Languages of AI are…

  9. Prerequisites for Deriving Formal Specifications from Natural Language Requirements.

    DTIC Science & Technology

    1983-04-01

    International Joint Conference on Artificial Intell1ence, American Association for Artificial Intelligence, Mento Park, CA, 1981, 385-387. Mann, William C...Centering". Proceedings of the Seventh International Joint Conference on Artificial Intelligence, American Association for Artificial Intelligence, Mento

  10. Intelligent manufacturing: the challenge for manufacturing strategy in China in the 21st century--what we will do

    NASA Astrophysics Data System (ADS)

    Yang, Shuzi; Lei, Ming; Guan, Zai-Lin; Xiong, Youlun

    1995-08-01

    This paper first introduces the project of intelligent manufacturing in China and the research state of the IIMRC (Intelligent and Integrated Manufacturing Research Centre) of HUST (Huazhong University of Science and Technology), then reviews the recent advances in object- oriented and distributed artificial intelligence and puts forth the view that these advances open up the prospect of systems that will enable the true integration of enterprises. In an attempt to identify domain requirements and match them with research achievements, the paper examines the current literature and distinguishes 14 features that are common. It argues that effective enterprise-wide support could be greatly facilitated by the existence of intelligent software entities with autonomous processing capabilities, that possess coordination and negotiation facilities and are organized in distributed hierarchical states.

  11. Artificial Intelligence--Applications in Education.

    ERIC Educational Resources Information Center

    Poirot, James L.; Norris, Cathleen A.

    1987-01-01

    This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

  12. AIonAI: a humanitarian law of artificial intelligence and robotics.

    PubMed

    Ashrafian, Hutan

    2015-02-01

    The enduring progression of artificial intelligence and cybernetics offers an ever-closer possibility of rational and sentient robots. The ethics and morals deriving from this technological prospect have been considered in the philosophy of artificial intelligence, the design of automatons with roboethics and the contemplation of machine ethics through the concept of artificial moral agents. Across these categories, the robotics laws first proposed by Isaac Asimov in the twentieth century remain well-recognised and esteemed due to their specification of preventing human harm, stipulating obedience to humans and incorporating robotic self-protection. However the overwhelming predominance in the study of this field has focussed on human-robot interactions without fully considering the ethical inevitability of future artificial intelligences communicating together and has not addressed the moral nature of robot-robot interactions. A new robotic law is proposed and termed AIonAI or artificial intelligence-on-artificial intelligence. This law tackles the overlooked area where future artificial intelligences will likely interact amongst themselves, potentially leading to exploitation. As such, they would benefit from adopting a universal law of rights to recognise inherent dignity and the inalienable rights of artificial intelligences. Such a consideration can help prevent exploitation and abuse of rational and sentient beings, but would also importantly reflect on our moral code of ethics and the humanity of our civilisation.

  13. Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider.

    PubMed

    Ashrafian, Hutan

    2017-04-01

    The potential for artificial intelligences and robotics in achieving the capacity of consciousness, sentience and rationality offers the prospect that these agents have minds. If so, then there may be a potential for these minds to become dysfunctional, or for artificial intelligences and robots to suffer from mental illness. The existence of artificially intelligent psychopathology can be interpreted through the philosophical perspectives of mental illness. This offers new insights into what it means to have either robot or human mental disorders, but may also offer a platform on which to examine the mechanisms of biological or artificially intelligent psychiatric disease. The possibility of mental illnesses occurring in artificially intelligent individuals necessitates the consideration that at some level, they may have achieved a mental capability of consciousness, sentience and rationality such that they can subsequently become dysfunctional. The deeper philosophical understanding of these conditions in mankind and artificial intelligences might therefore offer reciprocal insights into mental health and mechanisms that may lead to the prevention of mental dysfunction.

  14. Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

    PubMed

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2017-01-01

    Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds. Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  15. Instructional Applications of Artificial Intelligence.

    ERIC Educational Resources Information Center

    Halff, Henry M.

    1986-01-01

    Surveys artificial intelligence and the development of computer-based tutors and speculates on the future of artificial intelligence in education. Includes discussion of the definitions of knowledge, expert systems (computer systems that solve tough technical problems), intelligent tutoring systems (ITS), and specific ITSs such as GUIDON, MYCIN,…

  16. Artificial Intelligence and Autonomy: Opportunities and Challenges

    DTIC Science & Technology

    2017-10-01

    Cleared for Public Release Artificial Intelligence & Autonomy Opportunities and Challenges Andrew Ilachinski October 2017 Copyright © 2017 CNA... Artificial Intelligence & Autonomy Opportunities and 5a. CONTRACT NUMBER N00014-16-D-5003 Challenges 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0605154N...conducted by unmanned and increasingly autonomous weapon systems. This exploratory study considers the state-of-the-art of artificial intelligence (AI

  17. Artificial Intelligence Information Sources for the Beginner and Expert

    DTIC Science & Technology

    1991-05-01

    SUBPLEETAR TMS T bepbhdi" Artificial Intelligence ApplictionsforMlitar Expertis SystemsWilasbrVA 527Mrh 91 12a. DSCRIBTION C AIITY 6 STAEENRTY CTO SECb.T...DLSIFC ISTR BUMATION OC Apnclassified pu ncrlase; ituied inlsife unlimited. Artificial Intelligence Information Sources for the Beginner and Expert...mgivenfdsac.dia.mil UUCP: {...).osu-cisidsac!mgiven ABSTRACT A tremendous amount of information on artificial intelligence is available via different

  18. The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities

    NASA Astrophysics Data System (ADS)

    Muzyka, Kamil

    2013-12-01

    On the verge of technological breakthroughs, which define and revolutionize our understanding of intelligence, cognition, and personhood, especially when speaking of artificial intelligences and mind uploads, one must consider the legal implications of granting personhood rights to artificial intelligences or emulated human entities

  19. Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma.

    PubMed

    Rajpara, S M; Botello, A P; Townend, J; Ormerod, A D

    2009-09-01

    Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence. To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma. A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed. Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms. Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.

  20. Artificial Intelligence for Pathologists Is Not Near--It Is Here: Description of a Prototype That Can Transform How We Practice Pathology Tomorrow.

    PubMed

    Ye, Jay J

    2015-07-01

    Pathologists' daily tasks consist of both the professional interpretation of slides and the secretarial tasks of translating these interpretations into final pathology reports, the latter of which is a time-consuming endeavor for most pathologists. To describe an artificial intelligence that performs secretarial tasks, designated as Secretary-Mimicking Artificial Intelligence (SMILE). The underling implementation of SMILE is a collection of computer programs that work in concert to "listen to" the voice commands and to "watch for" the changes of windows caused by slide bar code scanning; SMILE responds to these inputs by acting upon PowerPath Client windows (Sunquest Information Systems, Tucson, Arizona) and its Microsoft Word (Microsoft, Redmond, Washington) Add-In window, eventuating in the reports being typed and finalized. Secretary-Mimicking Artificial Intelligence also communicates relevant information to the pathologist via the computer speakers and message box on the screen. Secretary-Mimicking Artificial Intelligence performs many secretarial tasks intelligently and semiautonomously, with rapidity and consistency, thus enabling pathologists to focus on slide interpretation, which results in a marked increase in productivity, decrease in errors, and reduction of stress in daily practice. Secretary-Mimicking Artificial Intelligence undergoes encounter-based learning continually, resulting in a continuous improvement in its knowledge-based intelligence. Artificial intelligence for pathologists is both feasible and powerful. The future widespread use of artificial intelligence in our profession is certainly going to transform how we practice pathology.

  1. Methodology Investigation of AI(Artificial Intelligence) Test Officer Support Tool. Volume 1

    DTIC Science & Technology

    1989-03-01

    American Association for Artificial inteligence A! ............. Artificial inteliigence AMC ............ Unt:ed States Army Maeriel Comand ASL...block number) FIELD GROUP SUB-GROUP Artificial Intelligence, Expert Systems Automated Aids to Testing 9. ABSTRACT (Continue on reverse if necessary and...identify by block number) This report covers the application of Artificial Intelligence-Techniques to the problem of creating automated tools to

  2. Conceptual Commitments of the LIDA Model of Cognition

    NASA Astrophysics Data System (ADS)

    Franklin, Stan; Strain, Steve; McCall, Ryan; Baars, Bernard

    2013-06-01

    Significant debate on fundamental issues remains in the subfields of cognitive science, including perception, memory, attention, action selection, learning, and others. Psychology, neuroscience, and artificial intelligence each contribute alternative and sometimes conflicting perspectives on the supervening problem of artificial general intelligence (AGI). Current efforts toward a broad-based, systems-level model of minds cannot await theoretical convergence in each of the relevant subfields. Such work therefore requires the formulation of tentative hypotheses, based on current knowledge, that serve to connect cognitive functions into a theoretical framework for the study of the mind. We term such hypotheses "conceptual commitments" and describe the hypotheses underlying one such model, the Learning Intelligent Distribution Agent (LIDA) Model. Our intention is to initiate a discussion among AGI researchers about which conceptual commitments are essential, or particularly useful, toward creating AGI agents.

  3. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    DOT National Transportation Integrated Search

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  4. Open ended intelligence: the individuation of intelligent agents

    NASA Astrophysics Data System (ADS)

    Weinbaum Weaver, David; Veitas, Viktoras

    2017-03-01

    Artificial general intelligence is a field of research aiming to distil the principles of intelligence that operate independently of a specific problem domain and utilise these principles in order to synthesise systems capable of performing any intellectual task a human being is capable of and beyond. While "narrow" artificial intelligence which focuses on solving specific problems such as speech recognition, text comprehension, visual pattern recognition and robotic motion has shown impressive breakthroughs lately, understanding general intelligence remains elusive. We propose a paradigm shift from intelligence perceived as a competence of individual agents defined in relation to an a priori given problem domain or a goal, to intelligence perceived as a formative process of self-organisation. We call this process open-ended intelligence. Starting with a brief introduction of the current conceptual approach, we expose a number of serious limitations that are traced back to the ontological roots of the concept of intelligence. Open-ended intelligence is then developed as an abstraction of the process of human cognitive development, so its application can be extended to general agents and systems. We introduce and discuss three facets of the idea: the philosophical concept of individuation, sense-making and the individuation of general cognitive agents. We further show how open-ended intelligence can be framed in terms of a distributed, self-organising network of interacting elements and how such process is scalable. The framework highlights an important relation between coordination and intelligence and a new understanding of values.

  5. Artificial Intelligence and Computer Assisted Instruction. CITE Report No. 4.

    ERIC Educational Resources Information Center

    Elsom-Cook, Mark

    The purpose of the paper is to outline some of the major ways in which artificial intelligence research and techniques can affect usage of computers in an educational environment. The role of artificial intelligence is defined, and the difference between Computer Aided Instruction (CAI) and Intelligent Computer Aided Instruction (ICAI) is…

  6. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part C: Basic AI topics

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1983-01-01

    Readily understandable overviews of search oriented problem solving, knowledge representation, and computational logic are provided. Mechanization, automation and artificial intelligence are discussed as well as how they interrelate.

  7. A Primer for Problem Solving Using Artificial Intelligence.

    ERIC Educational Resources Information Center

    Schell, George P.

    1988-01-01

    Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)

  8. An Overview of Production Systems

    DTIC Science & Technology

    1975-10-01

    DISTRIBUTED BY: Matonal Tochnica! Infonu srice U. S. DEPARTMENT OF COMMERCE 028143 Stanford Artificil Inteligence Laboratory October 1975 Memo AIM-271...ORGANIZATION NAMEL AND ADDRESS 18. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AE OKUI UBR Stanford University ARPA Order 249...014-64011I j SEC-jRITY CLASSIFICATION OF THIS PAGE (When, Data bHISP011 A Stanford Artificial ktteligncs Laboratory October 1975 Memo AIM-271 Computer

  9. Knowledge-based processing for aircraft flight control

    NASA Technical Reports Server (NTRS)

    Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul

    1994-01-01

    This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.

  10. 2017 Cybersecurity Workshop: Readouts from Working Groups - Video Text

    Science.gov Websites

    applicability of artificial intelligence to search for cybersecurity gaps in our existing SKATA networks. Second primarily renewable that all back each other up; that are all highly intelligent, artificial intelligence we have in cyber security, digital technologies, artificial intelligence. We think that that would

  11. Synthetic biology routes to bio-artificial intelligence.

    PubMed

    Nesbeth, Darren N; Zaikin, Alexey; Saka, Yasushi; Romano, M Carmen; Giuraniuc, Claudiu V; Kanakov, Oleg; Laptyeva, Tetyana

    2016-11-30

    The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular 'teachers' and 'students' is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). © 2016 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).

  12. Virtual Reality for Artificial Intelligence: human-centered simulation for social science.

    PubMed

    Cipresso, Pietro; Riva, Giuseppe

    2015-01-01

    There is a long last tradition in Artificial Intelligence as use of Robots endowing human peculiarities, from a cognitive and emotional point of view, and not only in shape. Today Artificial Intelligence is more oriented to several form of collective intelligence, also building robot simulators (hardware or software) to deeply understand collective behaviors in human beings and society as a whole. Modeling has also been crucial in the social sciences, to understand how complex systems can arise from simple rules. However, while engineers' simulations can be performed in the physical world using robots, for social scientist this is impossible. For decades, researchers tried to improve simulations by endowing artificial agents with simple and complex rules that emulated human behavior also by using artificial intelligence (AI). To include human beings and their real intelligence within artificial societies is now the big challenge. We present an hybrid (human-artificial) platform where experiments can be performed by simulated artificial worlds in the following manner: 1) agents' behaviors are regulated by the behaviors shown in Virtual Reality involving real human beings exposed to specific situations to simulate, and 2) technology transfers these rules into the artificial world. These form a closed-loop of real behaviors inserted into artificial agents, which can be used to study real society.

  13. Statistical Software and Artificial Intelligence: A Watershed in Applications Programming.

    ERIC Educational Resources Information Center

    Pickett, John C.

    1984-01-01

    AUTOBJ and AUTOBOX are revolutionary software programs which contain the first application of artificial intelligence to statistical procedures used in analysis of time series data. The artificial intelligence included in the programs and program features are discussed. (JN)

  14. Artificial intelligence in astronomy - a forecast.

    NASA Astrophysics Data System (ADS)

    Adorf, H. M.

    Since several years artificial intelligence techniques are being actively used in astronomy, particularly within the Hubble Space Telescope project. This contribution reviews achievements, analyses some problems of using artificial intelligence in an astronomical environment, and projects current AI programming trends into the future.

  15. In Pursuit of Artificial Intelligence.

    ERIC Educational Resources Information Center

    Watstein, Sarah; Kesselman, Martin

    1986-01-01

    Defines artificial intelligence and reviews current research in natural language processing, expert systems, and robotics and sensory systems. Discussion covers current commercial applications of artificial intelligence and projections of uses and limitations in library technical and public services, e.g., in cataloging and online information and…

  16. [Advances in the research of application of artificial intelligence in burn field].

    PubMed

    Li, H H; Bao, Z X; Liu, X B; Zhu, S H

    2018-04-20

    Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

  17. Analysis and Implementation of Robust Grasping Behaviors

    DTIC Science & Technology

    1990-05-01

    34 Technical Report 992, MIT Artificial Intelligence Laboratory, Cambridge, MA, May, 1987. 2. Brooks, R. A. "Achieving Artifci &l Intelligence Through...DTIu FILE COPY Technical Report 1237 ’Analysis and Implementation of NRobust Grasping Behaviors Camille Z. Chammas MIT Artificial Intelligence ...describes research conducted at the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the laboratory’s

  18. An Approach to Object Recognition: Aligning Pictorial Descriptions.

    DTIC Science & Technology

    1986-12-01

    PERFORMING 0RGANIZATION NAMIE ANDORS IS551. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREKA A WORK UNIT NUMBERS ( 545 Technology... ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo No. 931 December, 1986 AN APPROACH TO OBJECT RECOGNITION: ALIGNING PICTORIAL DESCRIPTIONS Shimon Ullman...within the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Support for the A.I. Laboratory’s artificial intelligence

  19. Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,

    DTIC Science & Technology

    1981-05-08

    STATEMENT ........................ 8 Artificial Intellegence Versus Supervisory Control ....... 8 Computer Generation of Operator Feedback...operator. Artificial Intelligence Versus Supervisory Control The use of computers to aid human operators can be divided into two catagories: artificial ...operator. Artificial intelligence ( A. I. ) attempts to give the computer maximum intelligence and to replace all operator functions by the computer

  20. Artificial Intelligence in Astronomy

    NASA Astrophysics Data System (ADS)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  1. The Artificial Intelligence Applications to Learning Programme.

    ERIC Educational Resources Information Center

    Williams, Noel

    1992-01-01

    Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

  2. Artificial Intelligence and Language Comprehension.

    ERIC Educational Resources Information Center

    National Inst. of Education (DHEW), Washington, DC. Basic Skills Group. Learning Div.

    The three papers in this volume concerning artificial intelligence and language comprehension were commissioned by the National Institute of Education to further the understanding of the cognitive processes that enable people to comprehend what they read. The first paper, "Artificial Intelligence and Language Comprehension," by Terry Winograd,…

  3. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    NASA Astrophysics Data System (ADS)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  4. A Research Program on Artificial Intelligence in Process Engineering.

    ERIC Educational Resources Information Center

    Stephanopoulos, George

    1986-01-01

    Discusses the use of artificial intelligence systems in process engineering. Describes a new program at the Massachusetts Institute of Technology which attempts to advance process engineering through technological advances in the areas of artificial intelligence and computers. Identifies the program's hardware facilities, software support,…

  5. Proceedings of the MIT/ONR Workshop on Distributed Communication and Decision Problems Motivated by Naval C3 Systems (2nd). Held in Monterey, California on 16-27 July 1979. Volume 2

    DTIC Science & Technology

    1980-03-01

    artificial intellegence methods to organize and control the system as well as to interpret surveillance data. • Surveillance and tracking of low-flying...algorithms and an artificial Intellegence approach to the processing and interpretation of the sensor data. At the very least we will consider how to...8:00-8:30 REGISTRATION 8:30-9:30 HALTING THE PROLIFERATION OF ERRORS - AN APPLICATION FOR ARTIFICIAL INTELLIGENCE Gerald Wilson, Senior Comcuter

  6. Transforming Systems Engineering through Model-Centric Engineering

    DTIC Science & Technology

    2018-02-28

    intelligence (e.g., Artificial Intelligence , etc.), because they provide a means for representing knowledge. We see these capabilities coming to use in both...level, including:  Performance is measured by degree of success of a mission  Artificial Intelligence (AI) is applied to counterparties so that they...Modeling, Artificial Intelligence , Simulation and Modeling, 1989. [140] SAE ARP4761. Guidelines and Methods for Conducting the Safety Assessment Process

  7. An Evaluation of the Generalized Intelligent Framework for Tutoring (GIFT) from an Author’s Perspective

    DTIC Science & Technology

    2014-12-01

    group instruction as effective as one - to- one tutoring. Educational Researcher. 1984;13(6):4–16. Carbonell. AI in CAI: an artificial intelligence...an official Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does...public release; distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Current US Army standards for training and education are group

  8. Dynamical Systems and Motion Vision.

    DTIC Science & Technology

    1988-04-01

    TASK Artificial Inteligence Laboratory AREA I WORK UNIT NUMBERS 545 Technology Square . Cambridge, MA 02139 C\\ II. CONTROLLING OFFICE NAME ANO0 ADDRESS...INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I.Memo No. 1037 April, 1988 Dynamical Systems and Motion Vision Joachim Heel Abstract: In this... Artificial Intelligence L3 Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory’s [1 Artificial Intelligence Research is

  9. Northeast Artificial Intelligence Consortium (NAIC). Volume 2. Discussing, Using, and Recognizing Plans

    DTIC Science & Technology

    1990-12-01

    knowledge and meta-reasoning. In Proceedings of EP14-85 ("Encontro Portugues de Inteligencia Artificial "), pages 138-154, Oporto, Portugal, 1985. [19] N, J...See reverse) 7. PERFORMING ORGANIZATION NAME(S) AND ADORESS(ES) 8. PERFORMING ORGANIZATION Northeast Artificial Intelligence...ABSTRACTM-2.,-- The Northeast Artificial Intelligence Consortium (NAIC) was created by the Air Force Systems Command, Rome Air Development Center, and

  10. Artificial Intelligence Study (AIS).

    DTIC Science & Technology

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  11. An analysis of the application of AI to the development of intelligent aids for flight crew tasks

    NASA Technical Reports Server (NTRS)

    Baron, S.; Feehrer, C.

    1985-01-01

    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

  12. Expertise, Task Complexity, and Artificial Intelligence: A Conceptual Framework.

    ERIC Educational Resources Information Center

    Buckland, Michael K.; Florian, Doris

    1991-01-01

    Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…

  13. Partial Bibliography of Work on Expert Systems,

    DTIC Science & Technology

    1982-12-01

    Bibliography: AAAI American Association for Artificial Intelligence ACM Association for Computing Machinery AFIPS American Federation of Information...Processing Societies ECAI European Conference on Artificial Intelligence IEEE Institute for Electrical and Electronic Engineers IFIPS International...Federation of Information Processing Societies IJCAI International Joint Conferences on Artificial Intelligence SIGPLAN ACM Special Interest Group on

  14. A Constructive Induction Approach to Computer Immunology

    DTIC Science & Technology

    1999-03-01

    LVM98] Lamont, Gary B., David A. Van Veldhuizen , and Robert E Marmelstein, A Distributed Architecture for a Self-Adaptive Computer Virus...Artificial Intelligence, Herndon, VA, 1995. [MVL98] Marmelstein, Robert E., David A. Van Veldhuizen , and Gary B. Lamont. Modeling & Analysis

  15. Intelligent web agents for a 3D virtual community

    NASA Astrophysics Data System (ADS)

    Dave, T. M.; Zhang, Yanqing; Owen, G. S. S.; Sunderraman, Rajshekhar

    2003-08-01

    In this paper, we propose an Avatar-based intelligent agent technique for 3D Web based Virtual Communities based on distributed artificial intelligence, intelligent agent techniques, and databases and knowledge bases in a digital library. One of the goals of this joint NSF (IIS-9980130) and ACM SIGGRAPH Education Committee (ASEC) project is to create a virtual community of educators and students who have a common interest in comptuer graphics, visualization, and interactive techniqeus. In this virtual community (ASEC World) Avatars will represent the educators, students, and other visitors to the world. Intelligent agents represented as specially dressed Avatars will be available to assist the visitors to ASEC World. The basic Web client-server architecture of the intelligent knowledge-based avatars is given. Importantly, the intelligent Web agent software system for the 3D virtual community is implemented successfully.

  16. The Case for Artificial Intelligence in Medicine

    PubMed Central

    Reggia, James A.

    1983-01-01

    Current artificial intelligence (AI) technology can be viewed as producing “systematic artifacts” onto which we project an interpretation of intelligent behavior. One major benefit this technology could bring to medicine is help with handling the tremendous and growing volume of medical knowledge. The reader is led to a vision of the medical library of tomorrow, an interactive, artificially intelligent knowledge source that is fully and directly integrated with daily patient care.

  17. Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

    DTIC Science & Technology

    1988-03-01

    logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

  18. List of ARI Conference Papers, Journal Articles, Books, and Book Chapters: 1982-1991

    DTIC Science & Technology

    1992-10-01

    and Engineering Applications of Artificial Intelligence and Expert Systems, Tullahoma, TN. Goehring, D.J., & Hart, R.J. (1985, October). Automated...systems: Computkr-based authoring. Proceedings of the 30th annual meeting of the Artificial Intelligence Society, Dayton, OH. Knapp, D.J., & Pliske, R.M...Moses, F.L. (1984-85) Intelligence vehicle integrated displays. Paper presented at the Conference on Applied Artificial Intelligence , the Data Processing

  19. Knowledge-Based Software Development Tools

    DTIC Science & Technology

    1993-09-01

    GREEN, C., AND WESTFOLD, S. Knowledge-based programming self-applied. In Machine Intelligence 10, J. E. Hayes, D. Mitchie, and Y. Pao, Eds., Wiley...Technical Report KES.U.84.2, Kestrel Institute, April 1984. [181 KORF, R. E. Toward a model of representation changes. Artificial Intelligence 14, 1...Artificial Intelligence 27, 1 (February 1985), 43-96. Replinted in Readings in Artificial Intelligence and Software Engineering, C. Rich •ad R. Waters

  20. The application of connectionism to query planning/scheduling in intelligent user interfaces

    NASA Technical Reports Server (NTRS)

    Short, Nicholas, Jr.; Shastri, Lokendra

    1990-01-01

    In the mid nineties, the Earth Observing System (EOS) will generate an estimated 10 terabytes of data per day. This enormous amount of data will require the use of sophisticated technologies from real time distributed Artificial Intelligence (AI) and data management. Without regard to the overall problems in distributed AI, efficient models were developed for doing query planning and/or scheduling in intelligent user interfaces that reside in a network environment. Before intelligent query/planning can be done, a model for real time AI planning and/or scheduling must be developed. As Connectionist Models (CM) have shown promise in increasing run times, a connectionist approach to AI planning and/or scheduling is proposed. The solution involves merging a CM rule based system to a general spreading activation model for the generation and selection of plans. The system was implemented in the Rochester Connectionist Simulator and runs on a Sun 3/260.

  1. What Is Artificial Intelligence Anyway?

    ERIC Educational Resources Information Center

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  2. Cooperation and the evolution of intelligence

    PubMed Central

    McNally, Luke; Brown, Sam P.; Jackson, Andrew L.

    2012-01-01

    The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the ‘social intelligence hypothesis’), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa. PMID:22496188

  3. Visiting Scholars Program

    DTIC Science & Technology

    2016-09-01

    other associated grants. 15. SUBJECT TERMS SUNY Poly, STEM, Artificial Intelligence , Command and Control 16. SECURITY CLASSIFICATION OF: 17...neuromorphic system has the potential to be widely used in a high-efficiency artificial intelligence system. Simulation results have indicated that the...novel multiresolution fusion and advanced fusion performance evaluation tool for an Artificial Intelligence based natural language annotation engine for

  4. The Joint Tactical Aerial Resupply Vehicle Impact on Sustainment Operations

    DTIC Science & Technology

    2017-06-09

    Artificial Intelligence , Sustainment Operations, Rifle Company, Autonomous Aerial Resupply, Joint Tactical Autonomous Aerial Resupply System 16...Integrations and Development System AI Artificial Intelligence ARCIC Army Capabilities Integration Center ARDEC Armament Research, Development and...semi- autonomous systems, and fully autonomous systems. Autonomy of machines depends on sophisticated software, including Artificial Intelligence

  5. Artificial Intelligence Measurement System, Overview and Lessons Learned. Final Project Report.

    ERIC Educational Resources Information Center

    Baker, Eva L.; Butler, Frances A.

    This report summarizes the work conducted for the Artificial Intelligence Measurement System (AIMS) Project which was undertaken as an exploration of methodology to consider how the effects of artificial intelligence systems could be compared to human performance. The research covered four areas of inquiry: (1) natural language processing and…

  6. The Potential of Artificial Intelligence in Aids for the Disabled.

    ERIC Educational Resources Information Center

    Boyer, John J.

    The paper explores the possibilities for applying the knowledge of artificial intelligence (AI) research to aids for the disabled. Following a definition of artificial intelligence, the paper reviews areas of basic AI research, such as computer vision, machine learning, and planning and problem solving. Among application areas relevant to the…

  7. Computer science, artificial intelligence, and cybernetics: Applied artificial intelligence in Japan

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

    Rubinger, B.

    1988-01-01

    This sourcebook provides information on the developments in artificial intelligence originating in Japan. Spanning such innovations as software productivity, natural language processing, CAD, and parallel inference machines, this volume lists leading organizations conducting research or implementing AI systems, describes AI applications being pursued, illustrates current results achieved, and highlights sources reporting progress.

  8. The importance of motivation and emotion for explaining human cognition.

    PubMed

    Güss, C Dominik; Dörner, Dietrich

    2017-01-01

    Lake et al. discuss building blocks of human intelligence that are quite different from those of artificial intelligence. We argue that a theory of human intelligence has to incorporate human motivations and emotions. The interaction of motivation, emotion, and cognition is the real strength of human intelligence and distinguishes it from artificial intelligence.

  9. Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

    DTIC Science & Technology

    1989-10-01

    Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

  10. The 1990 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  11. Artificial Intelligence Applications to High-Technology Training.

    ERIC Educational Resources Information Center

    Dede, Christopher

    1987-01-01

    Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

  12. Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

    PubMed

    Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

    2017-12-01

    To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

  13. A Methodology to Assess UrbanSim Scenarios

    DTIC Science & Technology

    2012-09-01

    Education LOE – Line of Effort MMOG – Massively Multiplayer Online Game MC3 – Maneuver Captain’s Career Course MSCCC – Maneuver Support...augmented reality simulations, increased automation and artificial intelligence simulation, and massively multiplayer online games (MMOG), among...distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Turn-based strategy games and simulations are vital tools for military

  14. Artificial intelligence and synthetic biology: A tri-temporal contribution.

    PubMed

    Bianchini, Francesco

    2016-10-01

    Artificial intelligence can make numerous contributions to synthetic biology. I would like to suggest three that are related to the past, present and future of artificial intelligence. From the past, works in biology and artificial systems by Turing and von Neumann prove highly interesting to explore within the new framework of synthetic biology, especially with regard to the notions of self-modification and self-replication and their links to emergence and the bottom-up approach. The current epistemological inquiry into emergence and research on swarm intelligence, superorganisms and biologically inspired cognitive architecture may lead to new achievements on the possibilities of synthetic biology in explaining cognitive processes. Finally, the present-day discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of notions such as "life", "cognition", "artificial" and "natural", as well as their interconnections in theoretical synthetic biology. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. Protecting Networks Via Automated Defense of Cyber Systems

    DTIC Science & Technology

    2016-09-01

    autonomics, and artificial intelligence . Our conclusion is that automation is the future of cyber defense, and that advances are being made in each of...SUBJECT TERMS Internet of Things, autonomics, sensors, artificial intelligence , cyber defense, active cyber defense, automated indicator sharing...called Automated Defense of Cyber Systems, built upon three core technological components: sensors, autonomics, and artificial intelligence . Our

  16. Automated Knowledge Generation with Persistent Surveillance Video

    DTIC Science & Technology

    2008-03-26

    5 2.1 Artificial Intelligence . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Formal Logic . . . . . . . . . . . . . . . . . . . 6 2.1.2...background of Artificial Intelligence and the reasoning engines that will be applied to generate knowledge from data. Section 2.2 discusses background on...generation from persistent video. 4 II. Background In this chapter, we will discuss the background of Artificial Intelligence, Semantic Web, image

  17. Finding Edges and Lines in Images.

    DTIC Science & Technology

    1983-06-01

    34 UNCLASSI FlED , SECURITY CLASSIFICATION OF THIS PAGE ("osen Data Entered) READ INSTRUCTIONSREPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM I. REPORT...PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA&WORKUNITNUMBERS 545 Technology Square...in the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory’s artificial intelligence research

  18. Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

    DTIC Science & Technology

    1986-10-01

    rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

  19. Planning and Scheduling of Software Manufacturing Projects

    DTIC Science & Technology

    1991-03-01

    based on the previous results in social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing...planning and scheduling, and the traditional approaches to planning in artificial intelligence, and extends the techniques that have been developed by them...social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing planning and scheduling, and the

  20. Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

    DTIC Science & Technology

    1987-10-01

    include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

  1. Real Rules of Inference

    DTIC Science & Technology

    1986-01-01

    the AAAI Workshop on Uncertainty and Probability in Artificial Intelligence , 1985. [McC771 McCarthy, J. "Epistemological Problems of Aritificial ...NUMBER OF PAGES Artificial Intelligence , Data Fusion, Inference, Probability, 30 Philosophy, Inheritance Hierachies, Default Reasoning ia.PRCECODE I...prominent philosophers Glymour and Thomason even applaud the uninhibited steps: Artificial Intelligence has done us the service not only of reminding us

  2. Current Uses of Artificial Intelligence in Special Education. Abstract XI: Research & Resources on Special Education.

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

    Summarized are two reports of a federally funded project on the use of artificial intelligence in special education. The first report, "Artificial Intelligence Applications in Special Education: How Feasible?," by Alan Hofmeister and Joseph Ferrara, provides information on the development and evaluation of a series of prototype systems in special…

  3. Cultural Modelling: Literature review

    DTIC Science & Technology

    2006-09-01

    of mood and/or emotions. Our review did show some evidence that artificial intelligence research has tended to depict human decision making as...pp. 72-79). The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB). Halfill, T., Sundstrom, E., Nielsen, T. M...M. & Thagard, P. (2005). Changing personalities: Towards realistic virtual characters. Journal of Experimental & Theoretical Artificial Intelligence

  4. "It's Going to Kill Us!" and Other Myths about the Future of Artificial Intelligence

    ERIC Educational Resources Information Center

    Atkinson, Robert D.

    2016-01-01

    Given the promise that artificial intelligence (AI) holds for economic growth and societal advancement, it is critical that policymakers not only avoid retarding the progress of AI innovation, but also actively support its further development and use. This report provides a primer on artificial intelligence and debunks five prevailing myths that,…

  5. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    ERIC Educational Resources Information Center

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  6. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    ERIC Educational Resources Information Center

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  7. ESD/MITRE Software Acquisition Symposium Proceedings; an ESD/Industry Dialogue held in Bedford, Massachusetts on May 6-7, 1986

    DTIC Science & Technology

    1986-05-07

    Cycle? Moderator: Christine M. Anderson Dennis D. Doe Manager of Engineering Software and Artificial Intelligence Boeing Aerospace Company In... intelligence systems development pro- cess affect the life cycle? Artificial intelligence developers seem to be the last haven for people who don’t...of Engineering Software and Artificial Intelligence at the Boeing Aerospace Company. In this capacity, Mr. Doe is the focal point for software

  8. Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

    DTIC Science & Technology

    1988-04-13

    Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

  9. Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

    DTIC Science & Technology

    1983-09-01

    AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

  10. First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

    NASA Technical Reports Server (NTRS)

    Griffin, Sandy (Editor)

    1987-01-01

    Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered.

  11. Mobile Agents Applications.

    ERIC Educational Resources Information Center

    Martins, Rosane Maria; Chaves, Magali Ribeiro; Pirmez, Luci; Rust da Costa Carmo, Luiz Fernando

    2001-01-01

    Discussion of the need to filter and retrieval relevant information from the Internet focuses on the use of mobile agents, specific software components which are based on distributed artificial intelligence and integrated systems. Surveys agent technology and discusses the agent building package used to develop two applications using IBM's Aglet…

  12. A Distributed Artificial Intelligence Approach To Object Identification And Classification

    NASA Astrophysics Data System (ADS)

    Sikka, Digvijay I.; Varshney, Pramod K.; Vannicola, Vincent C.

    1989-09-01

    This paper presents an application of Distributed Artificial Intelligence (DAI) tools to the data fusion and classification problem. Our approach is to use a blackboard for information management and hypothe-ses formulation. The blackboard is used by the knowledge sources (KSs) for sharing information and posting their hypotheses on, just as experts sitting around a round table would do. The present simulation performs classification of an Aircraft(AC), after identifying it by its features, into disjoint sets (object classes) comprising of the five commercial ACs; Boeing 747, Boeing 707, DC10, Concord and Boeing 727. A situation data base is characterized by experimental data available from the three levels of expert reasoning. Ohio State University ElectroScience Laboratory provided this experimental data. To validate the architecture presented, we employ two KSs for modeling the sensors, aspect angle polarization feature and the ellipticity data. The system has been implemented on Symbolics 3645, under Genera 7.1, in Common LISP.

  13. A Challenge to Watson

    ERIC Educational Resources Information Center

    Detterman, Douglas K.

    2011-01-01

    Watson's Jeopardy victory raises the question of the similarity of artificial intelligence and human intelligence. Those of us who study human intelligence issue a challenge to the artificial intelligence community. We will construct a unique battery of tests for any computer that would provide an actual IQ score for the computer. This is the same…

  14. Space applications of artificial intelligence; 1990 Goddard Conference, Greenbelt, MD, May 1, 2, 1990, Selected Papers

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1990-01-01

    The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.

  15. Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

    DTIC Science & Technology

    1984-12-01

    system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD

  16. A Cyber Situational Awareness Model for Network Administrators

    DTIC Science & Technology

    2017-03-01

    environments, the Internet of Things, artificial intelligence , and so on. As users’ data requirements grow more complex, they demand information...security of systems of interest. Further, artificial intelligence is a powerful concept in information technology. Therefore, new research should...look into how to use artificial intelligence to develop CSA. Human interaction with cyber systems is not making networks and their components safer

  17. Operations Monitoring Assistant System Design

    DTIC Science & Technology

    1986-07-01

    Logic. Artificial Inteligence 25(1)::75-94. January.18. 41 -Nils J. Nilsson. Problem-Solving Methods In Artificli Intelligence. .klcG raw-Hill B3ook...operations monitoring assistant (OMA) system is designed that combines operations research, artificial intelligence, and human reasoning techniques and...KnowledgeCraft (from Carnegie Group), and 5.1 (from Teknowledze). These tools incorporate the best methods of applied artificial intelligence, and

  18. The 1994 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Hostetter, Carl F. (Editor)

    1994-01-01

    This publication comprises the papers presented at the 1994 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/GSFC, Greenbelt, Maryland, on 10-12 May 1994. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  19. Artificial Intelligence and Its Potential as an Aid to Vocational Training and Education.

    ERIC Educational Resources Information Center

    Aleksander, I.; And Others

    This document contains a series of papers which attempt to de-mystify the subject of artificial intelligence and to show how some countries in the European Community (EC) are approaching the promotion of development and application of artificial intelligence systems that can be used as an aid in vocational training programs, as well as to…

  20. The Classification, Detection and Handling of Imperfect Theory Problems.

    DTIC Science & Technology

    1987-04-20

    Explanation-Based Learning: Failure-Driven Schema Refinement." Proceedings of the Third IEEE Conference on Artificial Intelligence Applications . Orlando...A. Rajamoney. Gerald F. DeJong Artificial Intelligence Research Group " . Coordinated Science Laboratory " University of Illinois at Urbana-Champaign...Urbana. IL 61801 . April 1987 ABSTRACT This paper also appears in the Proceedings of the Tenth International Conference on Artificial Intelligence

  1. Interdisciplinary Study on Artificial Intelligence.

    DTIC Science & Technology

    1983-07-01

    systems, uiophysics of information processing, cognitive science, and traditional artificial intelligence. The objective behi d this objective was to...information processing, cognitive science, and traditional * artificial intelligence. The objective behind this objective was to provide a vehicle for reviewing...Another departure from ’classical’ neurodynamics must be sought in the strong coupling between the micro and macroscopic scales. No other physical mechanism

  2. The 1993 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Hostetter, Carl F. (Editor)

    1993-01-01

    This publication comprises the papers presented at the 1993 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, MD on May 10-13, 1993. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  3. Organisational Structure and Information Technology (IT): Exploring the Implications of IT for Future Military Structures

    DTIC Science & Technology

    2006-07-01

    4 Abbreviations AI Artificial Intelligence AM Artificial Memory CAD Computer Aided...memory (AM), artificial intelligence (AI), and embedded knowledge systems it is possible to expand the “effective span of competence” of...Technology J Joint J2 Joint Intelligence J3 Joint Operations NATO North Atlantic Treaty Organisation NCW Network Centric Warfare NHS National Health

  4. Patient behavior and the benefits of artificial intelligence: the perils of "dangerous" literacy and illusory patient empowerment.

    PubMed

    Schulz, Peter J; Nakamoto, Kent

    2013-08-01

    Artificial intelligence can provide important support of patient health. However, limits to realized benefits can arise as patients assume an active role in their health decisions. Distinguishing the concepts of health literacy and patient empowerment, we analyze conditions that bias patient use of the Internet and limit access to and impact of artificial intelligence. Improving health literacy in the face of the Internet requires significant guidance. Patients must be directed toward the appropriate tools and also provided with key background knowledge enabling them to use the tools and capitalize on the artificial intelligence technology. Benefits of tools employing artificial intelligence to promote health cannot be realized without recognizing and addressing the patients' desires, expectations, and limitations that impact their Internet behavior. In order to benefit from artificial intelligence, patients need a substantial level of background knowledge and skill in information use-i.e., health literacy. It is critical that health professionals respond to patient search for information on the Internet, first by guiding their search to relevant, authoritative, and responsive sources, and second by educating patients about how to interpret the information they are likely to encounter. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  5. Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

    ERIC Educational Resources Information Center

    Yaratan, Huseyin

    2003-01-01

    An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

  6. Northeast Artificial Intelligence Consortium Annual Report for 1987. Volume 5. Building an Intelligent Assistant: The Acquisition, Integration, and Maintenance of Complex Distributed Tasks

    DTIC Science & Technology

    1989-03-01

    resolved through global or local (associated with specific nodes) conflict resolution strategies.$ One solution is to order the arcs in the set... according to their specificity and to execute the first triggered arc. In this way, the most specific subsuming situation will be preferred over other...priority; another says that random questions should be discouraged. In such a case a non-conventional resolution mechanism must be used to resolve the

  7. Modern Hardware Technologies and Software Techniques for On-Line Database Storage and Access.

    DTIC Science & Technology

    1985-12-01

    of the information in a message narrative. This method employs artificial intelligence techniques to extract information, In simalest terms, an...disf ribif ion (tape replacemenf) systemns Database distribution On-fine mass storage Videogame ROM (luke-box I Media Cost Mt $2-10/438 $10-SO/G38...trajninq ot tne great intelligence for the analyst would be required. If, on’ the other hand, a sentence analysis scneme siTole enouq,. for the low-level

  8. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    DTIC Science & Technology

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  9. Importance of nonverbal expression to the emergence of emotive artificial intelligence systems

    NASA Astrophysics Data System (ADS)

    Pioggia, Giovanni; Hanson, David; Dinelli, Serena; Di Francesco, Fabio; Francesconi, R.; De Rossi, Danilo

    2002-07-01

    The nonverbal expression of the emotions, especially in the human face, has rapidly become an area of intense interest in computer science and robotics. Exploring the emotions as a link between external events and behavioural responses, artificial intelligence designers and psychologists are approaching a theoretical understanding of foundational principles which will be key to the physical embodiment of artificial intelligence. In fact, it has been well demonstrated that many important aspects of intelligence are grounded in intimate communication with the physical world- so-called embodied intelligence . It follows naturally, then, that recent advances in emotive artificial intelligence show clear and undeniable broadening in the capacities of biologically-inspired robots to survive and thrive in a social environment. The means by which AI may express its foundling emotions are clearly integral to such capacities. In effect: powerful facial expressions are critical to the development of intelligent, sociable robots. Following discussion the importance of the nonverbal expression of emotions in humans and robots, this paper describes methods used in robotically emulating nonverbal expressions using human-like robotic faces. Furthermore, it describes the potentially revolutionary impact of electroactive polymer (EAP) actuators as artificial muscles for such robotic devices.

  10. Spontaneous Analogy by Piggybacking on a Perceptual System

    DTIC Science & Technology

    2013-08-01

    1992). High-level Perception, Representation, and Analogy: A Critique of Artificial Intelligence Methodology. J. Exp. Theor. Artif . Intell., 4(3...nrl.navy.mil David W. Aha Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory (Code 5510); Washington, DC 20375 david.aha...Research Laboratory,Center for Applied Research in Artificial Intelligence (Code 5510),4555 Overlook Ave., SW,Washington,DC,20375 8. PERFORMING ORGANIZATION

  11. Circumscribing Circumscription. A Guide to Relevance and Incompleteness,

    DTIC Science & Technology

    1985-10-01

    other rules of conjecture, to account for resource limitations. P "- h’ MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A.I. Memo...of conjecture, to account for resource limitations. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts...Institute of Technology. Support for the laboratory’s artificial intelligence research is provided in part by the Advanced Research Projects Agency

  12. Why the United States Must Adopt Lethal Autonomous Weapon Systems

    DTIC Science & Technology

    2017-05-25

    2017. http://www.designboom.com/ technology /designboom-tech-predictions-robotics-12-26- 2016/. Egan, Matt. "Robots Write Thousands Of News Stories A...views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture sees artificial intelligence as an economic savior...Army, 37 pages. The East and West have differing views on the morality of artificial intelligence (AI) and robotics technology . Eastern culture

  13. Survey of Intelligent Computer-Aided Training

    NASA Technical Reports Server (NTRS)

    Loftin, R. B.; Savely, Robert T.

    1992-01-01

    Intelligent Computer-Aided Training (ICAT) systems integrate artificial intelligence and simulation technologies to deliver training for complex, procedural tasks in a distributed, workstation-based environment. Such systems embody both the knowledge of how to perform a task and how to train someone to perform that task. This paper briefly reviews the antecedents of ICAT systems and describes the approach to their creation developed at the NASA Lyndon B. Johnson Space Center. In addition to the general ICAT architecture, specific ICAT applications that have been or are currently under development are discussed. ICAT systems can offer effective solutions to a number of training problems of interest to the aerospace community.

  14. Application of decentralized cooperative problem solving in dynamic flexible scheduling

    NASA Astrophysics Data System (ADS)

    Guan, Zai-Lin; Lei, Ming; Wu, Bo; Wu, Ya; Yang, Shuzi

    1995-08-01

    The object of this study is to discuss an intelligent solution to the problem of task-allocation in shop floor scheduling. For this purpose, the technique of distributed artificial intelligence (DAI) is applied. Intelligent agents (IAs) are used to realize decentralized cooperation, and negotiation is realized by using message passing based on the contract net model. Multiple agents, such as manager agents, workcell agents, and workstation agents, make game-like decisions based on multiple criteria evaluations. This procedure of decentralized cooperative problem solving makes local scheduling possible. And by integrating such multiple local schedules, dynamic flexible scheduling for the whole shop floor production can be realized.

  15. Building intelligent systems: Artificial intelligence research at NASA Ames Research Center

    NASA Technical Reports Server (NTRS)

    Friedland, P.; Lum, H.

    1987-01-01

    The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a truly autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

  16. Building intelligent systems - Artificial intelligence research at NASA Ames Research Center

    NASA Technical Reports Server (NTRS)

    Friedland, Peter; Lum, Henry

    1987-01-01

    The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a 'truly' autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.

  17. THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

    DTIC Science & Technology

    COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

  18. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    DOT National Transportation Integrated Search

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  19. Artificial intelligence in robot control systems

    NASA Astrophysics Data System (ADS)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  20. A Progress Report on Artificial Intelligence: Hospital Applications and a Review of the Artificial Intelligence Marketplace

    PubMed Central

    Brenkus, Lawrence M.

    1984-01-01

    Artificial intelligence applications are finally beginning to move from the university research laboratory into commercial use. Before the end of the century, this new computer technology will have profound effects on our work, economy, and lives. At present, relatively few products have appeared in the hospital, but we can anticipate significant product offerings in instrumentation and affecting hospital administration within 5 years.

  1. A Spoken English Recognition Expert System.

    DTIC Science & Technology

    1983-09-01

    Davidson. "Representation of Knowledge," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A. Felgenbaum. DTIC document number AD...Regents of the University of CalTorni, 1981. 9. Gardner, Anne. "Search," Handbook of Artificial Intelligence, edited by Avron Barr and Edward A...Felgenbaum, DTIC document number AD A074078, 1979. 10. Gardner, Anne,et al. "Natural Language Understanding," Handbook of Artificial Intelligence, edited

  2. Active Ambiguity Reduction: An Experiment Design Approach to Tractable Qualitative Reasoning.

    DTIC Science & Technology

    1987-04-20

    Approach to Tractable Qualitative Reasoning Shankar A. Rajamoney t [ For Gerald F. DeJong Artificial Intelligence Research Group Coordinated Science...Representations of Knowledge in a Mechanics Problem- Solver." Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Cambridge. MIA...International Joint Conference on Artificial Intelligence. Tokyo. Japan. 1979. [de Kleer84] J. de Kleer and J. S. Brown. "A Qualitative Physics Based on

  3. Strategic Computing. New-Generation Computing Technology: A Strategic Plan for Its Development and Application to Critical Problems in Defense

    DTIC Science & Technology

    1983-10-28

    Computing. By seizing an opportunity to leverage recent advances in artificial intelligence, computer science, and microelectronics, the Agency plans...occurred in many separated areas of artificial intelligence, computer science, and microelectronics. Advances in "expert system" technology now...and expert knowledge o Advances in Artificial Intelligence: Mechanization of speech recognition, vision, and natural language understanding. o

  4. The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

    NASA Technical Reports Server (NTRS)

    Hostetter, Carl F. (Editor)

    1995-01-01

    This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed.

  5. Defense Information Systems Program Automated CORDIVEM Design Requirements,

    DTIC Science & Technology

    1984-02-28

    for the Soviet military organization and equipment. Dr. John Spagnuolo incorporated artificial intelligence techniques in the discussion of functional...4-44 4.1.2.18.2 Artificial Intelligence ...... ........ 4-49 4.1.2.18.3 Types of A.I ................. 4-51 4.1.2.19 General Planning Requirements...described later. Further, some subprocesses may need one of the various techniques associated with the broad field of Artificial Intelligence (A.I.) in

  6. [The application and development of artificial intelligence in medical diagnosis systems].

    PubMed

    Chen, Zhencheng; Jiang, Yong; Xu, Mingyu; Wang, Hongyan; Jiang, Dazong

    2002-09-01

    This paper has reviewed the development of artificial intelligence in medical practice and medical diagnostic expert systems, and has summarized the application of artificial neural network. It explains that a source of difficulty in medical diagnostic system is the co-existence of multiple diseases--the potentially inter-related diseases. However, the difficulty of image expert systems is inherent in high-level vision. And it increases the complexity of expert system in medical image. At last, the prospect for the development of artificial intelligence in medical image expert systems is made.

  7. Artificial Intelligence.

    ERIC Educational Resources Information Center

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  8. Artificial Immune Algorithm for Subtask Industrial Robot Scheduling in Cloud Manufacturing

    NASA Astrophysics Data System (ADS)

    Suma, T.; Murugesan, R.

    2018-04-01

    The current generation of manufacturing industry requires an intelligent scheduling model to achieve an effective utilization of distributed manufacturing resources, which motivated us to work on an Artificial Immune Algorithm for subtask robot scheduling in cloud manufacturing. This scheduling model enables a collaborative work between the industrial robots in different manufacturing centers. This paper discussed two optimizing objectives which includes minimizing the cost and load balance of industrial robots through scheduling. To solve these scheduling problems, we used the algorithm based on Artificial Immune system. The parameters are simulated with MATLAB and the results compared with the existing algorithms. The result shows better performance than existing.

  9. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    PubMed

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  10. Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

    PubMed Central

    Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

  11. Deploying an Intelligent Pairing Assistant for Air Operation Centers

    DTIC Science & Technology

    2016-06-23

    primary contributions of this case study are applying artificial intelligence techniques to a novel domain and discussing the software evaluation...their standard workflows. The primary contributions of this case study are applying artificial intelligence techniques to a novel domain and...users for more efficient and accurate pairing? Participants Participants in the evaluation consisted of three SMEs employed at Intelligent Software

  12. Northeast Artificial Intelligence Consortium Annual Report - 1988 Parallel Vision. Volume 9

    DTIC Science & Technology

    1989-10-01

    supports the Northeast Aritificial Intelligence Consortium (NAIC). Volume 9 Parallel Vision Report submitted by Christopher M. Brown Randal C. Nelson...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT - 1988 Parallel Vision Syracuse University Christopher M. Brown and Randal C. Nelson...Technical Director Directorate of Intelligence & Reconnaissance FOR THE COMMANDER: IGOR G. PLONISCH Directorate of Plans & Programs If your address has

  13. Artificial intelligence approaches to astronomical observation scheduling

    NASA Technical Reports Server (NTRS)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  14. Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

    DTIC Science & Technology

    2016-06-01

    research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

  15. Artificial intelligence in nanotechnology.

    PubMed

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  16. Artificial intelligence in nanotechnology

    NASA Astrophysics Data System (ADS)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  17. Application of Artificial Intelligence for Bridge Deterioration Model.

    PubMed

    Chen, Zhang; Wu, Yangyang; Li, Li; Sun, Lijun

    2015-01-01

    The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

  18. Application of Artificial Intelligence for Bridge Deterioration Model

    PubMed Central

    Chen, Zhang; Wu, Yangyang; Sun, Lijun

    2015-01-01

    The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention. PMID:26601121

  19. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part A: The core ingredients

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. The goal of Artificial Intelligence is focused on developing computational approaches to intelligent behavior. This goal is so broad - covering virtually all aspects of human cognitive activity - that substantial confusion has arisen as to the actual nature of AI, its current status and its future capability. This volume, the first in a series of NBS/NASA reports on the subject, attempts to address these concerns. Thus, this report endeavors to clarify what AI is, the foundations on which it rests, the techniques utilized, applications, the participants and, finally, AI's state-of-the-art and future trends. It is anticipated that this report will prove useful to government and private engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

  20. Computer Intelligence: Unlimited and Untapped.

    ERIC Educational Resources Information Center

    Staples, Betsy

    1983-01-01

    Herbert Simon (Nobel prize-winning economist/professor) expresses his views on human and artificial intelligence, problem solving, inventing concepts, and the future. Includes comments on expert systems, state of the art in artificial intelligence, robotics, and "Bacon," a computer program that finds scientific laws hidden in raw data.…

  1. Expert Systems and Special Education.

    ERIC Educational Resources Information Center

    Hofmeister, Alan M.; Ferrara, Joseph M.

    The application of artificial intelligence to the problems of education is examined. One of the most promising areas in artificial intelligence is expert systems technology which engages the user in a problem-solving diaglogue. Some of the characteristics that make expert systems "intelligent" are identified and exemplified. The rise of…

  2. Artificial Intelligence Applications for Education: Promise, ...Promises.

    ERIC Educational Resources Information Center

    Adams, Dennis M.; Hamm, Mary

    1988-01-01

    Surveys the current status of artificial intelligence (AI) technology. Discusses intelligent tutoring systems, robotics, and applications for educators. Likens the status of AI at present to that of aviation in the very early 1900s. States that educators need to be involved in future debates concerning AI. (CW)

  3. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    NASA Technical Reports Server (NTRS)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  4. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    NASA Technical Reports Server (NTRS)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  5. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 5. Building an Intelligent Assistant: The Acquisition, Integration, and Maintenance of Complex Distributed Tasks

    DTIC Science & Technology

    1988-06-01

    extraction nets. TerrainMaps: Tools for physical and pseudo-physical molding and growing of features on terrain and thematic maps. 5-13 + ,m , mmmmmm mmmmm...ok 1) the student neem confused, and 2) the teot for wroag-answerstshold is met Recognizing a confused tudent is admittedly a mabjective and imprecise...you know that GRADE in iine 9 is a control variable? Student: Yes 2. Tutor: OIL What i the value of GRADE at anytime during loop execution? Studam

  6. Northeast Artificial Intelligence Consortium Annual Report 1986. Volume 4. Part A. Hierarchical Region-Based Approach to Automatic Photointerpretation. Part B. Application of AI Techniques to Image Segmentation and Region Identification

    DTIC Science & Technology

    1988-01-01

    MONITORING ORGANIZATION Northeast Artificial (If applicaole)nelincCostum(AcRome Air Development Center (COCU) Inteligence Consortium (NAIC)I 6c. ADDRESS...f, Offell RADC-TR-88-1 1, Vol IV (of eight) Interim Technical ReportS June 1988 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1986...13441-5700 EMENT NO NO NO ACCESSION NO62702F 5 8 71 " " over) I 58 27 13 " ൓ TITLE (Include Security Classification) NORTHEAST ARTIFICIAL INTELLIGENCE

  7. Artificial Neural Networks and Instructional Technology.

    ERIC Educational Resources Information Center

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  8. Artificial Intelligence and Educational Technology: A Natural Synergy. Extended Abstract.

    ERIC Educational Resources Information Center

    McCalla, Gordon I.

    Educational technology and artificial intelligence (AI) are natural partners in the development of environments to support human learning. Designing systems with the characteristics of a rich learning environment is the long term goal of research in intelligent tutoring systems (ITS). Building these characteristics into a system is extremely…

  9. Applications of Artificial Intelligence in Education--A Personal View.

    ERIC Educational Resources Information Center

    Richer, Mark H.

    1985-01-01

    Discusses: how artificial intelligence (AI) can advance education; if the future of software lies in AI; the roots of intelligent computer-assisted instruction; protocol analysis; reactive environments; LOGO programming language; student modeling and coaching; and knowledge-based instructional programs. Numerous examples of AI programs are cited.…

  10. A Computer-Aided Instruction Program for Teaching the TOPS20-MM Facility on the DDN (Defense Data Network)

    DTIC Science & Technology

    1988-06-01

    Continue on reverse if necessary and identify by block number) FIELD GROUP SUB-GROUP Computer Assisted Instruction; Artificial Intelligence 194...while he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been...he/she tries to perform given tasks. Means-ends analysis, a classic technique for solving search problems in Artificial Intelligence, has been used

  11. How Computers Are Used in the Teaching of Music and Speculations about How Artificial Intelligence Could Be Applied to Radically Improve the Learning of Compositional Skills. CITE Report No. 6.

    ERIC Educational Resources Information Center

    Holland, Simon

    This paper forms part of a preliminary survey for work on the application of artificial intelligence theories and techniques to the learning of music composition skills. The paper deals with present day applications of computers to the teaching of music and speculations about how artificial intelligence might be used to foster music composition in…

  12. An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

    NASA Technical Reports Server (NTRS)

    Gevarter, W. B.

    1983-01-01

    Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

  13. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

    PubMed Central

    Contreras, Ivan

    2018-01-01

    Background Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. Objective The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. Methods A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. Results We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. Conclusions We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life. PMID:29848472

  14. Center for Artificial Intelligence

    DTIC Science & Technology

    1992-03-14

    builder’s intelligent assistant. The basic approach of IGOR is to integrate the complementary strategies of exploratory and confirmatory data analysis...Recovery: A Model and Experiments," in Proceedings of the Ninth National Conference on Artifcial Intelligence , Anaheim, CA, July 1991, pp. 801-808. Howe...Lehnert University of Massachusetts, Amherst, MAJ (413) 545-1322 Lessei•:s.umass.edu Title: Center for Artificial Intelligence Contract #: N00014-86-K

  15. Space station data system analysis/architecture study. Task 5: Program plan

    NASA Technical Reports Server (NTRS)

    1985-01-01

    Cost estimates for both the on-board and ground segments of the Space Station Data System (SSDS) are presented along with summary program schedules. Advanced technology development recommendations are provided in the areas of distributed data base management, end-to-end protocols, command/resource management, and flight qualified artificial intelligence machines.

  16. Philosophical and Socio-Cognitive Foundations for Teaching in Higher Education through Collaborative Approaches to Student Learning

    ERIC Educational Resources Information Center

    Jones, Adrian

    2011-01-01

    This paper considers the implications for higher education of recent work on narrative theory, distributed cognition and artificial intelligence. These perspectives are contrasted with the educational implications of Heidegger's ontological phenomenology [being-there and being-aware (Da-sein)] and with the classic and classical foundations of…

  17. Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

    PubMed

    Das, Nilakash; Topalovic, Marko; Janssens, Wim

    2018-03-01

    The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.

  18. Integrated human-machine intelligence in space systems.

    PubMed

    Boy, G A

    1992-07-01

    This paper presents an artificial intelligence approach to integrated human-machine intelligence in space systems. It discusses the motivations for Intelligent Assistant Systems in both nominal and abnormal situations. The problem of constructing procedures is shown to be a very critical issue. In particular, keeping procedural experience in both design and operation is critical. We suggest what artificial intelligence can offer in this direction. Some crucial problems induced by this approach are discussed in detail. Finally, we analyze the various roles that would be shared by both astronauts, ground operators, and the intelligent assistant system.

  19. Artificial intelligence approaches for rational drug design and discovery.

    PubMed

    Duch, Włodzisław; Swaminathan, Karthikeyan; Meller, Jarosław

    2007-01-01

    Pattern recognition, machine learning and artificial intelligence approaches play an increasingly important role in rational drug design, screening and identification of candidate molecules and studies on quantitative structure-activity relationships (QSAR). In this review, we present an overview of basic concepts and methodology in the fields of machine learning and artificial intelligence (AI). An emphasis is put on methods that enable an intuitive interpretation of the results and facilitate gaining an insight into the structure of the problem at hand. We also discuss representative applications of AI methods to docking, screening and QSAR studies. The growing trend to integrate computational and experimental efforts in that regard and some future developments are discussed. In addition, we comment on a broader role of machine learning and artificial intelligence approaches in biomedical research.

  20. Artificial intelligence: the clinician of the future.

    PubMed

    Gallagher, S M

    2001-09-01

    Human beings have long been fascinated with the idea of artificial intelligence. This fascination is fueled by popular films such as Stanley Kubrick's 2001: A Space Odyssey and Stephen Spielberg's recent film, AI. However intriguing artificial intelligence may be, Hubert and Spencer Dreyfus contend that qualities exist that are uniquely human--the qualities thought to be inaccessible to the computer "mind." Patricia Benner further investigated the qualities that guide clinicians in making decisions and assessments that are not entirely evidence-based or grounded in scientific data. Perhaps it is the intuitive nature of the human being that separates us from the machine. The state of artificial intelligence is described herein, along with a discussion of computerized clinical decision-making and the role of the human being in these decisions.

  1. [Artificial intelligence--the knowledge base applied to nephrology].

    PubMed

    Sancipriano, G P

    2005-01-01

    The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

  2. Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

    PubMed

    Tajmir, Shahein H; Alkasab, Tarik K

    2018-06-01

    Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  3. Artificial intelligent e-learning architecture

    NASA Astrophysics Data System (ADS)

    Alharbi, Mafawez; Jemmali, Mahdi

    2017-03-01

    Many institutions and university has forced to use e learning, due to its ability to provide additional and flexible solutions for students and researchers. E-learning In the last decade have transported about the extreme changes in the distribution of education allowing learners to access multimedia course material at any time, from anywhere to suit their specific needs. In the form of e learning, instructors and learners live in different places and they do not engage in a classroom environment, but within virtual universe. Many researches have defined e learning based on their objectives. Therefore, there are small number of e-learning architecture have proposed in the literature. However, the proposed architecture has lack of embedding intelligent system in the architecture of e learning. This research argues that unexplored potential remains, as there is scope for e learning to be intelligent system. This research proposes e-learning architecture that incorporates intelligent system. There are intelligence components, which built into the architecture.

  4. Possible Conflicts, ARRs, and Conflicts

    DTIC Science & Technology

    2002-05-04

    Fourteenth European Conference on Artificial Intelligence Inteligencia Artificial , 41-53, (2001). (ECAI 2000), pp. 136-140, Berlin, Germany, (2000). [31] B...introduced), or proach to model-based diagnosis within the Artificial Intelligence backward (when a discrepancy is found, such as in CAEN [2, 21], community... Artificial Intelli- Relations (ARRs for short), for fault detection and localization [34]. gence community (usually known as DX). It is a research

  5. An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

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

    El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

    Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

  6. An Application of Artificial Intelligence to the Implementation of Electronic Commerce

    NASA Astrophysics Data System (ADS)

    Srivastava, Anoop Kumar

    In this paper, we present an application of Artificial Intelligence (AI) to the implementation of Electronic Commerce. We provide a multi autonomous agent based framework. Our agent based architecture leads to flexible design of a spectrum of multiagent system (MAS) by distributing computation and by providing a unified interface to data and programs. Autonomous agents are intelligent enough and provide autonomy, simplicity of communication, computation, and a well developed semantics. The steps of design and implementation are discussed in depth, structure of Electronic Marketplace, an ontology, the agent model, and interaction pattern between agents is given. We have developed mechanisms for coordination between agents using a language, which is called Virtual Enterprise Modeling Language (VEML). VEML is a integration of Java and Knowledge Query and Manipulation Language (KQML). VEML provides application programmers with potential to globally develop different kinds of MAS based on their requirements and applications. We have implemented a multi autonomous agent based system called VE System. We demonstrate efficacy of our system by discussing experimental results and its salient features.

  7. Artificial Intelligence and Expert Systems.

    ERIC Educational Resources Information Center

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  8. [Artificial intelligence in psychiatry-an overview].

    PubMed

    Meyer-Lindenberg, A

    2018-06-18

    Artificial intelligence and the underlying methods of machine learning and neuronal networks (NN) have made dramatic progress in recent years and have allowed computers to reach superhuman performance in domains that used to be thought of as uniquely human. In this overview, the underlying methodological developments that made this possible are briefly delineated and then the applications to psychiatry in three domains are discussed: precision medicine and biomarkers, natural language processing and artificial intelligence-based psychotherapeutic interventions. In conclusion, some of the risks of this new technology are mentioned.

  9. The Hospital of the Future. Megatrends, Driving Forces, Barriers to Implementation, Overarching Perspectives, Major Trends into the Future, Implications for TATRC And Specific Recommendations for Action

    DTIC Science & Technology

    2008-10-01

    Healthcare Systems Will Be Those That Work With Data/Info In New Ways • Artificial Intelligence Will Come to the Fore o Effectively Acquire...Education • Artificial Intelligence Will Assist in o History and Physical Examination o Imaging Selection via algorithms o Test Selection via algorithms...medical language into a simulation model based upon artificial intelligence , and • the content verification and validation of the cognitive

  10. Applications of artificial intelligence V; Proceedings of the Meeting, Orlando, FL, May 18-20, 1987

    NASA Technical Reports Server (NTRS)

    Gilmore, John F. (Editor)

    1987-01-01

    The papers contained in this volume focus on current trends in applications of artificial intelligence. Topics discussed include expert systems, image understanding, artificial intelligence tools, knowledge-based systems, heuristic systems, manufacturing applications, and image analysis. Papers are presented on expert system issues in automated, autonomous space vehicle rendezvous; traditional versus rule-based programming techniques; applications to the control of optional flight information; methodology for evaluating knowledge-based systems; and real-time advisory system for airborne early warning.

  11. Color regeneration from reflective color sensor using an artificial intelligent technique.

    PubMed

    Saracoglu, Ömer Galip; Altural, Hayriye

    2010-01-01

    A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

  12. AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

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

    Johnson, J.R.; Netrologic, Inc., San Diego, CA)

    1988-01-01

    Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

  13. Artificial Intelligence: Threat or Boon to Radiologists?

    PubMed

    Recht, Michael; Bryan, R Nick

    2017-11-01

    The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  14. Artificial Intelligence and Spacecraft Power Systems

    NASA Technical Reports Server (NTRS)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  15. The future of radiology augmented with Artificial Intelligence: A strategy for success.

    PubMed

    Liew, Charlene

    2018-05-01

    The rapid development of Artificial Intelligence/deep learning technology and its implementation into routine clinical imaging will cause a major transformation to the practice of radiology. Strategic positioning will ensure the successful transition of radiologists into their new roles as augmented clinicians. This paper describes an overall vision on how to achieve a smooth transition through the practice of augmented radiology where radiologists-in-the-loop ensure the safe implementation of Artificial Intelligence systems. Copyright © 2018 Elsevier B.V. All rights reserved.

  16. Conversion of the CALAP (Computer Aided Landform Analysis Program) Program from FORTRAN to DUCK.

    DTIC Science & Technology

    1986-09-01

    J’ DUCK artificial intelligence logic programming 20 AVrACT (Cthm m reerse stabN ameeaaW idelfr by block mbae) An expert advisor program named CALAP...original program was developed in FORTRAN on an HP- 1000, a mirticomputer. CALAP was reprogrammed in an Artificial Intelligence (AI) language called DUCK...the Artificial Intelligence Center, U.S. Army Engineer Topographic Laboratory, Fort Belvoir. Z" I. S. n- Page 1 I. Introduction An expert advisor

  17. Parallel Algorithms for Computer Vision.

    DTIC Science & Technology

    1989-01-01

    34 IEEE Tran. Pattern Ankyaij and Ma- Artifcial Intelligence , Tokyo, 1979. chine Intelligence , 6, 1984. Kirkpatrick, S., C.D. Gelatt, Jr. and M.P. Vecchi...MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T P06010 JAN 89 ETL-0529 UNCLASSIFIED DACA76-85-C-0010 F.’G 12/1I N mommiimmmiiso...PoggioI Massachusetts Institute of Technology i Artificial Intelligence Laboratory 545 Technology Square Cambridge, Massachusetts 02139 DTIC January

  18. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    ERIC Educational Resources Information Center

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in…

  19. Intelligent emissions controller for substance injection in the post-primary combustion zone of fossil-fired boilers

    DOEpatents

    Reifman, Jaques; Feldman, Earl E.; Wei, Thomas Y. C.; Glickert, Roger W.

    2003-01-01

    The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate. Based upon the optimal operating conditions from the optimization algorithms, the incremental substance cost per unit of emissions reduction, and the open-market price per unit of emissions reduction, the intelligent emissions controller allows for the determination of whether it is more cost-effective to achieve additional increments in emission reduction through the injection of additional substance or through the purchase of emission credits on the open market. This is of particular interest to fossil-fired electrical power plant operators. The intelligent emission controller is particularly adapted for determining the economical control of such pollutants as oxides of nitrogen (NO.sub.x) and carbon monoxide (CO) emitted by fossil-fired boilers by the selective introduction of multiple inputs of substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea, and combinations of these substances) above the primary combustion zone of fossil-fired boilers.

  20. Arguing Artificially: A Rhetorical Analysis of the Debates That Have Shaped Cognitive Science.

    ERIC Educational Resources Information Center

    Gibson, Keith

    2003-01-01

    Attempts a rhetorical analysis of the history of artificial intelligence research. Responds to scholarly needs in three areas: the rhetorical nature of science, the social construction of science knowledge, and the rhetorical strategies used in artificial intelligence (AI). Suggests that this work can help rhetoricians more accurately describe the…

  1. AIAA/NASA International Symposium on Space Information Systems, 2nd, Pasadena, CA, Sept. 17-19, 1990, Proceedings. Vols. 1 & 2

    NASA Technical Reports Server (NTRS)

    Tavenner, Leslie A. (Editor)

    1991-01-01

    These proceedings overview major space information system projects and lessons learned from current missions. Other topics include the science information system requirements for the 1990s, an information systems design approach for major programs, the technology needs and projections, the standards for space data information systems, the artificial intelligence technology and applications, international interoperability, and spacecraft data systems and architectures advanced communications. Other topics include the software engineering technology and applications, the multimission multidiscipline information system architectures, the distributed planning and scheduling systems and operations, and the computer and information systems architectures. Paper presented include prospects for scientific data analysis systems for solar-terrestrial physics in the 1990s, the Columbus data management system, data storage technologies for the future, the German aerospace research establishment, and launching artificial intelligence in NASA ground systems.

  2. Artificial intelligence: Learning to see and act

    NASA Astrophysics Data System (ADS)

    Schölkopf, Bernhard

    2015-02-01

    An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

  3. Bibliography: Artificial Intelligence.

    ERIC Educational Resources Information Center

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  4. Prediction model of dissolved oxygen in ponds based on ELM neural network

    NASA Astrophysics Data System (ADS)

    Li, Xinfei; Ai, Jiaoyan; Lin, Chunhuan; Guan, Haibin

    2018-02-01

    Dissolved oxygen in ponds is affected by many factors, and its distribution is unbalanced. In this paper, in order to improve the imbalance of dissolved oxygen distribution more effectively, the dissolved oxygen prediction model of Extreme Learning Machine (ELM) intelligent algorithm is established, based on the method of improving dissolved oxygen distribution by artificial push flow. Select the Lake Jing of Guangxi University as the experimental area. Using the model to predict the dissolved oxygen concentration of different voltage pumps, the results show that the ELM prediction accuracy is higher than the BP algorithm, and its mean square error is MSEELM=0.0394, the correlation coefficient RELM=0.9823. The prediction results of the 24V voltage pump push flow show that the discrete prediction curve can approximate the measured values well. The model can provide the basis for the artificial improvement of the dissolved oxygen distribution decision.

  5. Computational aerodynamics and artificial intelligence

    NASA Technical Reports Server (NTRS)

    Mehta, U. B.; Kutler, P.

    1984-01-01

    The general principles of artificial intelligence are reviewed and speculations are made concerning how knowledge based systems can accelerate the process of acquiring new knowledge in aerodynamics, how computational fluid dynamics may use expert systems, and how expert systems may speed the design and development process. In addition, the anatomy of an idealized expert system called AERODYNAMICIST is discussed. Resource requirements for using artificial intelligence in computational fluid dynamics and aerodynamics are examined. Three main conclusions are presented. First, there are two related aspects of computational aerodynamics: reasoning and calculating. Second, a substantial portion of reasoning can be achieved with artificial intelligence. It offers the opportunity of using computers as reasoning machines to set the stage for efficient calculating. Third, expert systems are likely to be new assets of institutions involved in aeronautics for various tasks of computational aerodynamics.

  6. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

    PubMed

    Contreras, Ivan; Vehi, Josep

    2018-05-30

    Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

  7. Simulation as an Engine of Physical Scene Understanding

    DTIC Science & Technology

    2013-11-05

    critical to the origins of intelligence : Researchers in developmental psychology, language, animal cognition, and artificial intelligence (2–6) con- sider...implemented computationally in classic artificial intelligence systems (18–20). However, these systems have not attempted to engage with physical scene un...N00014-09-0124, N00014-07-1-0937, and 1015GNA126; by Qualcomm; and by Intelligence Advanced Research Project Activity Grant D10PC20023. 1. Marr D (1982

  8. [Artificial intelligence in medicine: project of a mobile platform in an intelligent environment for the care of disabled and elderly people].

    PubMed

    Cortés, Ulises; Annicchiarico, Roberta; Campana, Fabio; Vázquez-Salceda, Javier; Urdiales, Cristina; Canãmero, Lola; López, Maite; Sánchez-Marrè, Miquel; Di Vincenzo, Sarah; Caltagirone, Carlo

    2004-04-01

    A project based on the integration of new technologies and artificial intelligence to develop a device--e-tool--for disabled patients and elderly people is presented. A mobile platform in intelligent environments (skilled-care facilities and home-care), controlled and managed by a multi-level architecture, is proposed to support patients and caregivers to increase self-dependency in activities of daily living.

  9. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare

    PubMed Central

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-01

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals. PMID:29464026

  10. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.

    PubMed

    Mamoshina, Polina; Ojomoko, Lucy; Yanovich, Yury; Ostrovski, Alex; Botezatu, Alex; Prikhodko, Pavel; Izumchenko, Eugene; Aliper, Alexander; Romantsov, Konstantin; Zhebrak, Alexander; Ogu, Iraneus Obioma; Zhavoronkov, Alex

    2018-01-19

    The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.

  11. A State Cyber Hub Operations Framework

    DTIC Science & Technology

    2016-06-01

    to communicate and sense or interact with their internal states or the external environment. Machine Learning: A type of artificial intelligence that... artificial intelligence , and computational linguistics concerned with the interactions between computers and human (natural) languages. Patching: A piece...formalizing a proof of concept for cyber initiatives and developed frameworks for operationalizing the data and intelligence produced across state

  12. Decision-Making and the Interface between Human Intelligence and Artificial Intelligence. AIR 1987 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Henard, Ralph E.

    Possible future developments in artificial intelligence (AI) as well as its limitations are considered that have implications for institutional research in higher education, and especially decision making and decision support systems. It is noted that computer software programs have been developed that store knowledge and mimic the decision-making…

  13. Experiments in Knowledge Refinement for a Large Rule-Based System

    DTIC Science & Technology

    1993-08-01

    empirical analysis to refine expert system knowledge bases. Aritificial Intelligence , 22:23-48, 1984. *! ...The Addison- Weslev series in artificial intelligence . Addison-Weslev. Reading, Massachusetts. 1981. Cooke, 1991: ttoger M. Cooke. Experts in...ment for classification systems. Artificial Intelligence , 35:197-226, 1988. 14 Overall, we believe that it will be possible to build a heuristic system

  14. The Potential Role of Artificial Intelligence Technology in Education.

    ERIC Educational Resources Information Center

    Salem, Abdel-Badeeh M.

    The field of Artificial Intelligence (AI) and Education has traditionally a technology-based focus, looking at the ways in which AI can be used in building intelligent educational software. In addition AI can also provide an excellent methodology for learning and reasoning from the human experiences. This paper presents the potential role of AI in…

  15. Hybrid Human-Computing Distributed Sense-Making: Extending the SOA Paradigm for Dynamic Adjudication and Optimization of Human and Computer Roles

    ERIC Educational Resources Information Center

    Rimland, Jeffrey C.

    2013-01-01

    In many evolving systems, inputs can be derived from both human observations and physical sensors. Additionally, many computation and analysis tasks can be performed by either human beings or artificial intelligence (AI) applications. For example, weather prediction, emergency event response, assistive technology for various human sensory and…

  16. Parallel Simulation of Subsonic Fluid Dynamics on a Cluster of Workstations.

    DTIC Science & Technology

    1994-11-01

    inside wind musical instruments. Typical simulations achieve $80\\%$ parallel efficiency (speedup/processors) using 20 HP-Apollo workstations. Detailed...TERMS AI, MIT, Artificial Intelligence, Distributed Computing, Workstation Cluster, Network, Fluid Dynamics, Musical Instruments 17. SECURITY...for example, the flow of air inside wind musical instruments. Typical simulations achieve 80% parallel efficiency (speedup/processors) using 20 HP

  17. An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants.

    PubMed

    Reifman, J; Feldman, E E; Wei, T Y; Glickert, R W

    2000-02-01

    The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.

  18. Demonstration of artificial intelligence technology for transit railcar diagnostics

    DOT National Transportation Integrated Search

    1999-01-01

    This report will be of interest to railcar maintenance professionals concerned with improving railcar maintenance fault-diagnostic capabilities through the use of artificial intelligence (AI) technologies. It documents the results of a demonstration ...

  19. Software Reviews. PC Software for Artificial Intelligence Applications.

    ERIC Educational Resources Information Center

    Epp, Helmut; And Others

    1988-01-01

    Contrasts artificial intelligence and conventional programming languages. Reviews Personal Consultant Plus, Smalltalk/V, and Nexpert Object, which are PC-based products inspired by problem-solving paradigms. Provides information on background and operation of each. (RT)

  20. Artificial Intelligence Assists Ultrasonic Inspection

    NASA Technical Reports Server (NTRS)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  1. In vitro and in vivo assessment of an intelligent artificial anal sphincter in rabbits.

    PubMed

    Huang, Zong-Hai; Shi, Fu-Jun; Chen, Fei; Liang, Fei-Xue; Li, Qiang; Yu, Jin-Long; Li, Zhou; Han, Xin-Jun

    2011-10-01

    Artificial sphincters have been developed for patients with fecal incontinence, but finding a way to make such sphincters more "intelligent" remains a problem. We assessed the function of a novel intelligent artificial anal sphincter (IAAS) in vitro and in vivo in rabbits. After the prosthesis was activated, rabbits were continent of feces during 81.4% of the activation time. The fecal detection unit provided 100% correct signals on stool in vitro and 65.7% in vivo. The results indicated that the IAAS could efficiently maintain continence and detect stool; however, the IAAS is still in the preliminary experimental stage and more work is needed to improve the system. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

  2. Artificial Intelligence (AI) Center of Excellence at the University of Pennsylvania

    DTIC Science & Technology

    1995-07-01

    that controls impact forces. Robust Location Estimation for MLR and Non-MLR Distributions (Dissertation Proposal) Gerda L. Kamberova MS-CIS-92-28...Bayesian Approach To Computer Vision Problems Gerda L. Kamberova MS-CIS-92-29 GRASP LAB 310 The object of our study is the Bayesian approach in...Estimation for MLR and Non-MLR Distributions (Dissertation) Gerda L. Kamberova MS-CIS-92-93 GRASP LAB 340 We study the problem of estimating an unknown

  3. Modeling and Evaluating Emotions Impact on Cognition

    DTIC Science & Technology

    2013-07-01

    Causality and Responsibility Judgment in Multi-Agent Interactions: Extended abstract. 23rd International Joint Conference on Artificial Inteligence ...responsibility judgment in multi-agent interactions." Journal of Artificial Intelligence Research v44(1), 223- 273. • Morteza Dehghani, Jonathan Gratch... Artificial Intelligence (AAAI’11). Grant related invited talks: • Keynote speaker, Workshop on Empathic and Emotional Agents at the International

  4. Optical Inference Machines

    DTIC Science & Technology

    1988-06-27

    de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

  5. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

    Harber, K.S.

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning bayesian expert system; a natural language generation system for a heterogeneous distributed database system; competence-switching'' managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

  6. Proceedings of the Seventh International Symposium on Methodologies for Intelligent Systems (Poster Session)

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

    Harber, K.S.

    1993-05-01

    This report contains the following papers: Implications in vivid logic; a self-learning Bayesian Expert System; a natural language generation system for a heterogeneous distributed database system; ``competence-switching`` managed by intelligent systems; strategy acquisition by an artificial neural network: Experiments in learning to play a stochastic game; viewpoints and selective inheritance in object-oriented modeling; multivariate discretization of continuous attributes for machine learning; utilization of the case-based reasoning method to resolve dynamic problems; formalization of an ontology of ceramic science in CLASSIC; linguistic tools for intelligent systems; an application of rough sets in knowledge synthesis; and a relational model for imprecise queries.more » These papers have been indexed separately.« less

  7. The 1988 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Rash, James (Editor); Hughes, Peter (Editor)

    1988-01-01

    This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools/methodologies.

  8. The role of artificial intelligence and expert systems in increasing STS operations productivity

    NASA Technical Reports Server (NTRS)

    Culbert, C.

    1985-01-01

    Artificial Intelligence (AI) is discussed. A number of the computer technologies pioneered in the AI world can make significant contributions to increasing STS operations productivity. Application of expert systems, natural language, speech recognition, and other key technologies can reduce manpower while raising productivity. Many aspects of STS support lend themselves to this type of automation. The artificial intelligence section of the mission planning and analysis division has developed a number of functioning prototype systems which demonstrate the potential gains of applying AI technology.

  9. Abstraction and reformulation in artificial intelligence.

    PubMed Central

    Holte, Robert C.; Choueiry, Berthe Y.

    2003-01-01

    This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653

  10. Abstraction and reformulation in artificial intelligence.

    PubMed

    Holte, Robert C; Choueiry, Berthe Y

    2003-07-29

    This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense.

  11. AAAI (American Association on Artificial Intelligence) Workshop on AI (Artificial Intelligence) Simulation Held in Philadelphia, Pennsylvania on August 11, 1986,

    DTIC Science & Technology

    1986-08-01

    is then applied in i ABSTRCT : ,.:,.vu knowledge acquisition from those multiple sources for a specific design, for example, an expert system for...67. N 181.1 47.U3 a75 269;9.6 % A. %3 3 Genetic Explanations: For the concept of a genetic explanation (see .d -. above) to apply to the Gaither...Simulation Research Unit (Acock,1985; Baker,1983; Baker,1985). -. MD’,EX srves as an inner shell for apPlying Artificial Intelligence and E:pert System

  12. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    PubMed

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

    Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

  13. Artificial intelligence in cardiology.

    PubMed

    Bonderman, Diana

    2017-12-01

    Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

  14. PRAIS: Distributed, real-time knowledge-based systems made easy

    NASA Technical Reports Server (NTRS)

    Goldstein, David G.

    1990-01-01

    This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

  15. Reflexive reasoning for distributed real-time systems

    NASA Technical Reports Server (NTRS)

    Goldstein, David

    1994-01-01

    This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.

  16. What Artificial Intelligence Is Doing for Training.

    ERIC Educational Resources Information Center

    Kirrane, Peter R.; Kirrane, Diane E.

    1989-01-01

    Discusses the three areas of research and application of artificial intelligence: (1) robotics, (2) natural language processing, and (3) knowledge-based or expert systems. Focuses on what expert systems can do, especially in the area of training. (JOW)

  17. Third Conference on Artificial Intelligence for Space Applications, part 2

    NASA Technical Reports Server (NTRS)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1988-01-01

    Topics relative to the application of artificial intelligence to space operations are discussed. New technologies for space station automation, design data capture, computer vision, neural nets, automatic programming, and real time applications are discussed.

  18. The coming of age of artificial intelligence in medicine.

    PubMed

    Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-05-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

  19. Tuberculosis control, and the where and why of artificial intelligence

    PubMed Central

    Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

    2017-01-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

  20. Artificial Intelligence in Cardiology.

    PubMed

    Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

    2018-06-12

    Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  1. The Coming of Age of Artificial Intelligence in Medicine*

    PubMed Central

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

  2. A review of European applications of artificial intelligence to space

    NASA Technical Reports Server (NTRS)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  3. Tuberculosis control, and the where and why of artificial intelligence.

    PubMed

    Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

    2017-04-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  4. Qualitative and Quantitative Proofs of Security Properties

    DTIC Science & Technology

    2013-04-01

    Naples, Italy (September 2012) – Australasian Joint Conference on Artifical Intelligence (December 2012). • Causality, Responsibility, and Blame...realistic solution concept, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), 2009, pp. 153–158. 17. J...Conference on Artificial Intelligence (AAAI-12), 2012, pp. 1917-1923. 29. J. Y. Halpern and S. Leung, Weighted sets of probabilities and minimax

  5. Bibliography of Research in Natural Language Generation

    DTIC Science & Technology

    1993-11-01

    on 1397] Barbara J. Gross Focuing and description in Artifcial Intelligence (GWAI-88), Geseke, West natural language dialogues, In Joshi et al. (557...Proceedings of the Fifth Canadian Conference from information in a frame structure. Data and on Artificial Intelligence , pages Ŕ-24, London, Knowledge...generation workshops (IWNLGS, ENLGWS), natural language processing conferences (ANLP, TINLAP, SPEECH), artificial intelligence conferences (AAAI, SCA

  6. High-Level Connectionist Models

    DTIC Science & Technology

    1993-04-01

    The Ohio State University, Columbus Ohio. To appearto Artifcial Life IlL Angeline, P., Saunders, G., Pollack, J. (1993). An evolutionary algorithm...of Robotics and Automation, 2(1):14-23. Brooks, R. A. (1991). Intelligence without representations. Artificial Intelligence , 47:139- 159. Connell, J. H...1990). Minimalist Mobile Robotics: A Colony-style Architecture for an Creature, Volume 5 of Perspectives in Artificial Intelligence . Academic Press

  7. Temporal Reasoning and Default Logics.

    DTIC Science & Technology

    1985-10-01

    Aritificial Intelligence ", Computer Science Research Report, Yale University, forthcoming (1985). . 74 .-, A Axioms for Describing Persistences and Clipping...34Circumscription - A Form of Non-Monotonic Reasoning", Artificial Intelligence , vol. 13 (1980), pp. 27-39. [13] McCarthy, John, "Applications of...and P. J. Hayes, "Some philosophical problems from the standpoint of artificial intelligence ", in: B. Meltzer and D. Michie (eds.), Machine

  8. Robot Programming.

    DTIC Science & Technology

    1982-12-01

    Paris, France, June, 1982, 519-530. Latoinbe, J. C. "Equipe Intelligence Artificielle et Robotique: Etat d’avancement des recherches," Laboratoire...8217AD-A127 233 ROBOT PROGRRMMING(U) MASSACHUSETTS INST OFGTECHi/ CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T LOZANO-PEREZ UNCLASSIFIED DC8 AI-9 N884...NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA I WORK UNIT NUMBERS ,. 545 Technology Square Cambridge

  9. Artificial intelligence applications in the intensive care unit.

    PubMed

    Hanson, C W; Marshall, B E

    2001-02-01

    To review the history and current applications of artificial intelligence in the intensive care unit. The MEDLINE database, bibliographies of selected articles, and current texts on the subject. The studies that were selected for review used artificial intelligence tools for a variety of intensive care applications, including direct patient care and retrospective database analysis. All literature relevant to the topic was reviewed. Although some of the earliest artificial intelligence (AI) applications were medically oriented, AI has not been widely accepted in medicine. Despite this, patient demographic, clinical, and billing data are increasingly available in an electronic format and therefore susceptible to analysis by intelligent software. Individual AI tools are specifically suited to different tasks, such as waveform analysis or device control. The intensive care environment is particularly suited to the implementation of AI tools because of the wealth of available data and the inherent opportunities for increased efficiency in inpatient care. A variety of new AI tools have become available in recent years that can function as intelligent assistants to clinicians, constantly monitoring electronic data streams for important trends, or adjusting the settings of bedside devices. The integration of these tools into the intensive care unit can be expected to reduce costs and improve patient outcomes.

  10. Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction.

    PubMed

    Park, Seong Ho; Han, Kyunghwa

    2018-03-01

    The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical images. Adoption of an artificial intelligence tool in clinical practice requires careful confirmation of its clinical utility. Herein, the authors explain key methodology points involved in a clinical evaluation of artificial intelligence technology for use in medicine, especially high-dimensional or overparameterized diagnostic or predictive models in which artificial deep neural networks are used, mainly from the standpoints of clinical epidemiology and biostatistics. First, statistical methods for assessing the discrimination and calibration performances of a diagnostic or predictive model are summarized. Next, the effects of disease manifestation spectrum and disease prevalence on the performance results are explained, followed by a discussion of the difference between evaluating the performance with use of internal and external datasets, the importance of using an adequate external dataset obtained from a well-defined clinical cohort to avoid overestimating the clinical performance as a result of overfitting in high-dimensional or overparameterized classification model and spectrum bias, and the essentials for achieving a more robust clinical evaluation. Finally, the authors review the role of clinical trials and observational outcome studies for ultimate clinical verification of diagnostic or predictive artificial intelligence tools through patient outcomes, beyond performance metrics, and how to design such studies. © RSNA, 2018.

  11. Artificial Intelligence for Controlling Robotic Aircraft

    NASA Technical Reports Server (NTRS)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  12. International experience on the use of artificial neural networks in gastroenterology.

    PubMed

    Grossi, E; Mancini, A; Buscema, M

    2007-03-01

    In this paper, we reconsider the scientific background for the use of artificial intelligence tools in medicine. A review of some recent significant papers shows that artificial neural networks, the more advanced and effective artificial intelligence technique, can improve the classification accuracy and survival prediction of a number of gastrointestinal diseases. We discuss the 'added value' the use of artificial neural networks-based tools can bring in the field of gastroenterology, both at research and clinical application level, when compared with traditional statistical or clinical-pathological methods.

  13. Toward a Theory of Representation Design

    DTIC Science & Technology

    1989-05-01

    understanding. This report describes research done at the Artificial Inteligence Laboratory of the Massachusetts Institute of Technology. Support for this...AD-A210 885 Technical Report 1128 Toward a Theory of Representation Design Jeffrey Van Baale MIT Artificial Intelligence Laboratory DTIC ELECTE A... Artificial Intelligence Laboratory 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME AND ADDRESS 11. REPORT DATE Advanced Research

  14. A Memory-Process Model of Symbolic Assimilation

    DTIC Science & Technology

    1974-04-01

    Systems: Final Report of a Study Group, published for Artificial Intellegence by North-Holland/Amorican...contribution of the methods is answered by evaluating the same program in the context of the field of artificial intelligence. The remainder of the...been widely demonstrated on a diversity of tasks in tha history of artificial intelligence. See [r.71], chapter 2. Given a particular task to be

  15. Supporting Organizational Problem Solving with a Workstation.

    DTIC Science & Technology

    1982-07-01

    G. [., and Sussman, G. J. AMORD: Explicit Control or Reasoning. In Proceedings of the Symposium on Artificial Intellignece and Programming Languagues...0505 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA& WORK UNIT NUMBERS 545...extending ideas from the field of Artificial Intelligence (A), we describ office work as a problem solving activity. A knowledge embedding language called

  16. Third Conference on Artificial Intelligence for Space Applications, part 1

    NASA Technical Reports Server (NTRS)

    Denton, Judith S. (Compiler); Freeman, Michael S. (Compiler); Vereen, Mary (Compiler)

    1987-01-01

    The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed.

  17. On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

    NASA Astrophysics Data System (ADS)

    Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

    2017-02-01

    Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

  18. Artificial intelligence: Learning to play Go from scratch

    NASA Astrophysics Data System (ADS)

    Singh, Satinder; Okun, Andy; Jackson, Andrew

    2017-10-01

    An artificial-intelligence program called AlphaGo Zero has mastered the game of Go without any human data or guidance. A computer scientist and two members of the American Go Association discuss the implications. See Article p.354

  19. Active vision in satellite scene analysis

    NASA Technical Reports Server (NTRS)

    Naillon, Martine

    1994-01-01

    In earth observation or planetary exploration it is necessary to have more and, more autonomous systems, able to adapt to unpredictable situations. This imposes the use, in artificial systems, of new concepts in cognition, based on the fact that perception should not be separated from recognition and decision making levels. This means that low level signal processing (perception level) should interact with symbolic and high level processing (decision level). This paper is going to describe the new concept of active vision, implemented in Distributed Artificial Intelligence by Dassault Aviation following a 'structuralist' principle. An application to spatial image interpretation is given, oriented toward flexible robotics.

  20. Model-Unified Planning and Execution for Distributed Autonomous System Control

    NASA Technical Reports Server (NTRS)

    Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

    2006-01-01

    The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

  1. Network Structures for Distributed Situation Assessment

    DTIC Science & Technology

    1980-08-01

    name a few-can contribute to the study of DAI. Presumably, DAI will advance these fields as well by providing a modeling technology suitable for precise...moreover, current SA sys- tems are highly centralized and vulnerable. Technological advances in cheap sen- sors, microprocessors, packet radio...communications, and artificial intelligence offer promising alternatives for performing military surveillance in many situations. A new approach now being

  2. Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic.

    PubMed

    Keramitsoglou, Iphigenia; Kiranoudis, Chris T; Maiheu, Bino; De Ridder, Koen; Daglis, Ioannis A; Manunta, Paolo; Paganini, Marc

    2013-10-01

    The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.

  3. Autonomous and Connected Vehicles: A Law Enforcement Primer

    DTIC Science & Technology

    2015-12-01

    CYBERSECURITY FOR AUTOMOBILES Intelligent Transportation Systems (ITS) that are emerging around the globe achieve that classification based on the convergence...Car Works,” October 18, 2011, IEEE Spectrum, http://spectrum.ieee.org/automaton/robotics/ artificial - intelligence /how-google-self-driving-car-works...whereby artificial intelligence acts on behalf of a human, but carries the same life or death consequences.435 States should encourage and engage in

  4. Complexity, Heuristic, and Search Analysis for the Games of Crossings and Epaminondas

    DTIC Science & Technology

    2014-03-27

    research in Artifical Intelligence (Section 2.1) and why games are studied (Section 2.2). Section 2.3 discusses how games are played and solved. An...5 2.1 Games in Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2 Game Study...Artificial Intelligence UCT Upper Confidence Bounds applied to Trees HUCT Heuristic Guided UCT LOA Lines of Action UCB Upper Confidence Bound RAVE Rapid

  5. Ontological Engineering and Mapping in Multiagent Systems Development

    DTIC Science & Technology

    2002-03-01

    for knowledge engineering or artificial intelligence . Nicola Guarino compares the various definitions and the differences in their meaning in...act upon the environment through effectors [Russel and Norvig 1995]. An intelligent agent is an agent that takes the best possible action in a...situation in order to accomplish its goals. Determining what exactly characterizes the best possible action splits the field of artificial intelligence

  6. Communication and Attitude Revision

    DTIC Science & Technology

    1992-01-01

    Conference on Aritificial Intelligence , (1989) 1074- 1079 3. Clark, H., Marshal, C.: Definite reference and mutual knowledge. In Joshi, A., Sag, I.. and...21st Annual Meeting of the ACL (1983) 57-63 9. Konolige, K.: On the relation between default and autoepistemic logic. Artificial Intelligence 35(3...reasoning. Artificial Intelligence 13 (1980) 81-132 16. Richmond Thomason. Accommodation, meaning, and implicature. In Cohen, P., Morgan, J., and

  7. Knowledge Based Consultation for Finite Element Structural Analysis.

    DTIC Science & Technology

    1980-05-01

    Intelligence Finite Element Program Tutorial 20 ABSTRACT (Continue. on rees side If necessary and ide.n’ty b,’ bit,, k nionh.) In recent years, techniques of...involved in Artificial Intelligence at Stanford University developed the program MYCIN F2], for clinical consultation of diseases that require...and Rules The basic backward chaining logic, characteristic to Artificial Intelligence . approaching 1he problem of knowledge representation was

  8. Parallel Logic Programming and Parallel Systems Software and Hardware

    DTIC Science & Technology

    1989-07-29

    Conference, Dallas TX. January 1985. (55) [Rous75] Roussel, P., "PROLOG: Manuel de Reference et d’Uilisation", Group d’ Intelligence Artificielle , Universite d...completed. Tools were provided for software development using artificial intelligence techniques. Al software for massively parallel architectures was...using artificial intelligence tech- niques. Al software for massively parallel architectures was started. 1. Introduction We describe research conducted

  9. Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

    PubMed

    Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

    2018-02-01

    Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising approaches for the prescription and monitoring of hemodialysis therapy. Current dialysis machines are continuously improving due to innovative technological developments, but patient safety is still a key challenge. Real-time monitoring systems, coupled with automatic instantaneous biofeedback, will allow changing dialysis prescriptions continuously. The integration of vital sign monitoring with dialysis parameters will produce large data sets that will require the use of data analysis techniques, possibly from the area of machine learning, in order to make better decisions and increase the safety of patients.

  10. Artificial Intelligence Techniques: Applications for Courseware Development.

    ERIC Educational Resources Information Center

    Dear, Brian L.

    1986-01-01

    Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

  11. An Artificial Intelligence Approach to Analyzing Student Errors in Statistics.

    ERIC Educational Resources Information Center

    Sebrechts, Marc M.; Schooler, Lael J.

    1987-01-01

    Describes the development of an artificial intelligence system called GIDE that analyzes student errors in statistics problems by inferring the students' intentions. Learning strategies involved in problem solving are discussed and the inclusion of goal structures is explained. (LRW)

  12. Ethical Implications of an Experiment in Artificial Intelligence.

    ERIC Educational Resources Information Center

    Levinson, Stephen E.

    2003-01-01

    Revisits the classic debate on whether there can be an artificial creation that behaves and uses language with intelligence and agency. Argues that many moral and spiritual objections to this notion are not grounded either ethically or empirically. (Author/VWL)

  13. Making Computers Smarter: A Look At the Controversial Field of Artificial Intelligence.

    ERIC Educational Resources Information Center

    Green, John O.

    1984-01-01

    Defines artificial intelligence (AI) and discusses its history; the current state of the art, research, experimentation, and practical applications; and probable future developments. Key dates in the history of AI and eight references are provided. (MBR)

  14. A Modular Artificial Intelligence Inference Engine System (MAIS) for support of on orbit experiments

    NASA Technical Reports Server (NTRS)

    Hancock, Thomas M., III

    1994-01-01

    This paper describes a Modular Artificial Intelligence Inference Engine System (MAIS) support tool that would provide health and status monitoring, cognitive replanning, analysis and support of on-orbit Space Station, Spacelab experiments and systems.

  15. 1988 Goddard Conference on Space Applications of Artificial Intelligence, Greenbelt, MD, May 24, 1988, Proceedings

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1988-01-01

    This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools methodologies.

  16. The Toulmin Argument Model in Artificial Intelligence

    NASA Astrophysics Data System (ADS)

    Verheij, Bart

    In 1958, Toulmin published The Uses of Argument. Although this anti-formalistic monograph initially received mixed reviews (see section 2 of [20] for Toulmin’s own recounting of the reception of his book), it has become a classical text on argumentation, and the number of references to the book (when writing these words1 —by a nice numerological coincidence—1958) continues to grow (see [7] and the special issue of Argumentation 2005; Vol. 19, No. 3). Also the field of Artificial Intelligence has discovered Toulmin’s work. Especially four of Toulmin’s themes have found follow-up in Artificial Intelligence.

  17. Northeast Artificial Intelligence Consortium Annual Report 1987. Volume 2, Part B. Discussing, Using, and Recognizing Plans

    DTIC Science & Technology

    1989-03-01

    1978. Williams. B.C. Qualitative Analysis of MOS Circuits. Artificial Inteligence . 1984. 24.. Wilson. K. From Association to Structure. Amsterdam:North...D-A208 378 RADC-TR-88-324, Vol II (of nine), Part B Interim Report March 1969 4. NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT 1987...II (of nine), Part B 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (ff ’aolicbl

  18. JPRS Report, East Europe

    DTIC Science & Technology

    1987-12-08

    34 artificial intelligence," on which we will also rely in the future, but once again, experience has shown that the smallest error in the construction...Western press presents such accidents as the transformation of the advantages of artificial intelligence into tragedies of artificial stupidity...life more tellingly than the recent studies con- cerning the ozone "void" discovered by satellites over the two poles, or the effects of the

  19. Adaptive Modeling and Real-Time Simulation

    DTIC Science & Technology

    1984-01-01

    34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

  20. LISP on a Reduced-Instruction-Set-Processor,

    DTIC Science & Technology

    1986-01-01

    Digital * Press, 1984. 19. Steele, G. L. Jr., and Sussman, G.J. LAMBDA : The Ultimate Imperative. Al Memo 353, MIT, Artificial ,, Inteligence Laboratory...procedure B is No 444, MIT Artificial Intelligence Laboratory, August, recursive, if procedure A can be reexecuted before the call 1977. returns. This...the programs Artificial Intelligence Programming. Lawrence Erlbaum use apply and eval, and of these three only frl uses eval Associates, Hillsdale, New

  1. A Multiagent Based Model for Tactical Planning

    DTIC Science & Technology

    2002-10-01

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

  2. High-Level Vision and Planning Workshop Proceedings

    DTIC Science & Technology

    1989-08-01

    Correspondence in Line Drawings of Multiple View-. In Proc. of 8th Intern. Joint Conf. on Artificial intellignece . 1983. [63] Tomiyasu, K. Tutorial...joint U.S.-Israeli workshop on artificial intelligence are provided in this Institute for Defense Analyses document. This document is based on a broad...participants is provided along with applicable references for individual papers. 14. SUBJECT TERMS 15. NUMBER OF PAGES Artificial Intelligence; Machine Vision

  3. Efficient Effects-Based Military Planning Final Report

    DTIC Science & Technology

    2010-11-13

    using probabilistic infer- ence methods,” in Proc. 8th Annu. Conf. Uncertainty Artificial Intelli - gence (UAI), Stanford, CA. San Mateo, CA: Morgan...Imprecise Probabilities, the 24th Conference on Uncertainty in Artificial Intelligence (UAI), 2008. 7. Yan Tong and Qiang Ji, Learning Bayesian Networks...Bayesian Networks using Constraints Cassio P. de Campos cassiopc@acm.org Dalle Molle Institute for Artificial Intelligence Galleria 2, Manno 6928

  4. Artificial Intelligence: A Selected Bibliography.

    ERIC Educational Resources Information Center

    Smith, Linda C., Comp.

    1984-01-01

    This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

  5. Artificial Intelligence in Speech Understanding: Two Applications at C.R.I.N.

    ERIC Educational Resources Information Center

    Carbonell, N.; And Others

    1986-01-01

    This article explains how techniques of artificial intelligence are applied to expert systems for acoustic-phonetic decoding, phonological interpretation, and multi-knowledge sources for man-machine dialogue implementation. The basic ideas are illustrated with short examples. (Author/JDH)

  6. Artificial Intelligence: Underlying Assumptions and Basic Objectives.

    ERIC Educational Resources Information Center

    Cercone, Nick; McCalla, Gordon

    1984-01-01

    Presents perspectives on methodological assumptions underlying research efforts in artificial intelligence (AI) and charts activities, motivations, methods, and current status of research in each of the major AI subareas: natural language understanding; computer vision; expert systems; search, problem solving, planning; theorem proving and logic…

  7. Artificial Intelligence and Expert Systems.

    ERIC Educational Resources Information Center

    Lawlor, Joseph

    Artificial intelligence (AI) is the field of scientific inquiry concerned with designing machine systems that can simulate human mental processes. The field draws upon theoretical constructs from a wide variety of disciplines, including mathematics, psychology, linguistics, neurophysiology, computer science, and electronic engineering. Some of the…

  8. Counseling, Artificial Intelligence, and Expert Systems.

    ERIC Educational Resources Information Center

    Illovsky, Michael E.

    1994-01-01

    Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

  9. Thinking, Creativity, and Artificial Intelligence.

    ERIC Educational Resources Information Center

    DeSiano, Michael; DeSiano, Salvatore

    This document provides an introduction to the relationship between the current knowledge of focused and creative thinking and artificial intelligence. A model for stages of focused and creative thinking gives: problem encounter/setting, preparation, concentration/incubation, clarification/generation and evaluation/judgment. While a computer can…

  10. A novel method for the production of core-shell microparticles by inverse gelation optimized with artificial intelligent tools.

    PubMed

    Rodríguez-Dorado, Rosalia; Landín, Mariana; Altai, Ayça; Russo, Paola; Aquino, Rita P; Del Gaudio, Pasquale

    2018-03-01

    Numerous studies have been focused on hydrophobic compounds encapsulation as oils. In fact, oils can provide numerous health benefits as synergic ingredient combined with other hydrophobic active ingredients. However, stable microparticles for pharmaceutical purposes are difficult to achieve when commonly techniques are used. In this work, sunflower oil was encapsulated in calcium-alginate capsules by prilling technique in co-axial configuration. Core-shell beads were produced by inverse gelation directly at the nozzle using a w/o emulsion containing aqueous calcium chloride solution in sunflower oil pumped through the inner nozzle while an aqueous alginate solution, coming out from the annular nozzle, produced the beads shell. To optimize process parameters artificial intelligence tools were proposed to optimize the numerous prilling process variables. Homogeneous and spherical microcapsules with narrow size distribution and a thin alginate shell were obtained when the parameters as w/o constituents, polymer concentrations, flow rates and frequency of vibration were optimized by two commercial software, FormRules® and INForm®, which implement neurofuzzy logic and Artificial Neural Networks together with genetic algorithms, respectively. This technique constitutes an innovative approach for hydrophobic compounds microencapsulation. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

    DTIC Science & Technology

    2017-10-01

    AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...finding solutions to compliment and supplement human analysts’ capacity, so intelligence and information can reach operators and end-users at the

  12. List of U.S. Army Research Institute Research and Technical Publications. Fiscal Year 2006

    DTIC Science & Technology

    2007-08-01

    performance support systems and computer-generated simulations powered by artificial intelligence , and super-broad bandwidth. We then present a set of...dialogue, Artificial Intelligence SBIR Phase I Report 61 FY 2006 Books and Book Chapters Durlach, P.J., Neuman, J.L., & Bowens, L.D...mediation of the social intelligence -social performance relationship by social knowledge, was supported for three out of five social performance

  13. The Analysis of Nominal Compounds,

    DTIC Science & Technology

    1985-12-01

    34Phenomenologically plausible parsing" in Proceedings of the 1984 American Association for Aritificial Intelligence Conference, pp. 335-339. 27 Wilensky, R...34December, 1985 - CPTM #8 LJ _DTIC -5ELECTE’ DEC 1 6 198M This series of internal memos describes research in E artificial intelligence conducted under...representational techniques for natural language that have evolved in linguistics and artificial intelligence , it is difficult to find much uniformity in the

  14. Issues in Adaptive Planning

    DTIC Science & Technology

    1986-06-30

    approach to the application of theorem proving to problem solving, Aritificial Intelligence 2 (1Q71), 18Q- 208. 4. Fikes, R., Hart, P. and Nilsson, N...by emphasizing the structure of knowledge. 1.2. Planning Literature The earliest work in planning in Artificial Intelligence grew out of the work on...References 1. Newell, A., Artificial Intelligence and the concept of mind, in Computer models of thought and language, Schank, R. and Colby, K. (editor

  15. Constraint-Directed Search: A Case Study of Job-Shop Scheduling.

    DTIC Science & Technology

    1983-12-13

    Structures But Were Unable to Represent", Proceedings of the American Association for Aritificial Intelligence , pp. 212-214, Stanford University...under these constraints raises a number of issues of interest to the artificial intelligence community such as: - knowledge representation semantics for...Management Science 15 2.3. Artificial Intelligence 17 2.4. Relationship to Previous Research 21 3. ISIS Modeling System 23 3.1. Introduction 24 3.2. Layer

  16. Framework for Evolutionary Development of an Autonomous Expert System for Acoustically Identifying Classifications of Vessels

    DTIC Science & Technology

    1989-01-01

    completely autonomous system. SOMMIIRE Une exp6rience en intelligence artificielle (IA) en cours au CRDA vise la misc au point 6ventuelle d’un syst~me...identifying vessel classifications from 0aaV Mcute SOAifatwgms is the ultimate goal of Artificial Intelligence (Al) wod ?bhig- eouaduted -*DRAR~ An...Friendly Interface ..................................................................... 4 3 Concepts of Assistant and Autonomous Artificially Intelligent

  17. Artificial intelligence - New tools for aerospace project managers

    NASA Technical Reports Server (NTRS)

    Moja, D. C.

    1985-01-01

    Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

  18. Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

    NASA Technical Reports Server (NTRS)

    1994-01-01

    The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments.

  19. Intelligent supercomputers: the Japanese computer sputnik

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

    Walter, G.

    1983-11-01

    Japan's government-supported fifth-generation computer project has had a pronounced effect on the American computer and information systems industry. The US firms are intensifying their research on and production of intelligent supercomputers, a combination of computer architecture and artificial intelligence software programs. While the present generation of computers is built for the processing of numbers, the new supercomputers will be designed specifically for the solution of symbolic problems and the use of artificial intelligence software. This article discusses new and exciting developments that will increase computer capabilities in the 1990s. 4 references.

  20. Finding Creativity in an Artificial Artist

    ERIC Educational Resources Information Center

    Norton, David; Heath, Derrall; Ventura, Dan

    2013-01-01

    Creativity is an important component of human intelligence, and imbuing artificially intelligent systems with creativity is an interesting challenge. In particular, it is difficult to quantify (or even qualify) creativity. Recently, it has been suggested that conditions for attributing creativity to a system include: appreciation, imagination, and…

  1. Artificial Intelligence and CALL.

    ERIC Educational Resources Information Center

    Underwood, John H.

    The potential application of artificial intelligence (AI) to computer-assisted language learning (CALL) is explored. Two areas of AI that hold particular interest to those who deal with language meaning--knowledge representation and expert systems, and natural-language processing--are described and examples of each are presented. AI contribution…

  2. The Art of Artificial Intelligence. 1. Themes and Case Studies of Knowledge Engineering

    DTIC Science & Technology

    1977-08-01

    in scientific and medical inference illuminate the art of knowledge engineering and its parent science , Artificial Intelligence....The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring

  3. Hybrid Applications Of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Borchardt, Gary C.

    1988-01-01

    STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

  4. Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

    ERIC Educational Resources Information Center

    Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

    2003-01-01

    Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

  5. Database in Artificial Intelligence.

    ERIC Educational Resources Information Center

    Wilkinson, Julia

    1986-01-01

    Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

  6. A Starter's Guide to Artificial Intelligence.

    ERIC Educational Resources Information Center

    McConnell, Barry A.; McConnell, Nancy J.

    1988-01-01

    Discussion of the history and development of artificial intelligence (AI) highlights a bibliography of introductory books on various aspects of AI, including AI programing; problem solving; automated reasoning; game playing; natural language; expert systems; machine learning; robotics and vision; critics of AI; and representative software. (LRW)

  7. Application of an artificial intelligence program to therapy of high-risk surgical patients.

    PubMed

    Patil, R S; Adibi, J; Shoemaker, W C

    1996-11-01

    We developed an artificial intelligence program from a large computerized database of hemodynamic and oxygen transport measurements together with prior studies defining survivors' values, outcome predictors, and a branched-chain decision tree. The artificial intelligence program was then tested on the data of 100 survivors and 100 nonsurvivors not used for the development of the program or other analyses. Using the predictor as a surrogate outcome measure, the therapy recommended by the program improved the predicted outcome 3.16% per therapeutic intervention while the actual therapy given increased outcome 1.86% in surviving patients; the artificial intelligence-recommended therapy improved outcome 7.9% in nonsurvivors, while the actual therapy given increased predicted outcome -0.29% in nonsurvivors (p < .05). There were fewer patients whose predicted outcome decreased after recommended treatment (14%) than after the actual therapy given (37%). Review of therapy recommended by the program did not reveal instances of inappropriate or potentially harmful recommendations.

  8. Teachers and artificial intelligence. The Logo connection.

    PubMed

    Merbler, J B

    1990-12-01

    This article describes a three-phase program for training special education teachers to teach Logo and artificial intelligence. Logo is derived from the LISP computer language and is relatively simple to learn and use, and it is argued that these factors make it an ideal tool for classroom experimentation in basic artificial intelligence concepts. The program trains teachers to develop simple demonstrations of artificial intelligence using Logo. The material that the teachers learn to teach is suitable as an advanced level topic for intermediate- through secondary-level students enrolled in computer competency or similar courses. The material emphasizes problem-solving and thinking skills using a nonverbal expressive medium (Logo), thus it is deemed especially appropriate for hearing-impaired children. It is also sufficiently challenging for academically talented children, whether hearing or deaf. Although the notion of teachers as programmers is controversial, Logo is relatively easy to learn, has direct implications for education, and has been found to be an excellent tool for empowerment-for both teachers and children.

  9. Artificial intelligence and robot responsibilities: innovating beyond rights.

    PubMed

    Ashrafian, Hutan

    2015-04-01

    The enduring innovations in artificial intelligence and robotics offer the promised capacity of computer consciousness, sentience and rationality. The development of these advanced technologies have been considered to merit rights, however these can only be ascribed in the context of commensurate responsibilities and duties. This represents the discernable next-step for evolution in this field. Addressing these needs requires attention to the philosophical perspectives of moral responsibility for artificial intelligence and robotics. A contrast to the moral status of animals may be considered. At a practical level, the attainment of responsibilities by artificial intelligence and robots can benefit from the established responsibilities and duties of human society, as their subsistence exists within this domain. These responsibilities can be further interpreted and crystalized through legal principles, many of which have been conserved from ancient Roman law. The ultimate and unified goal of stipulating these responsibilities resides through the advancement of mankind and the enduring preservation of the core tenets of humanity.

  10. Herbert: A Second Generation Mobile Robot.

    DTIC Science & Technology

    1988-01-01

    PROJECT. TASK S Artificial Inteligence Laboratory AREA A WORK UNIT NUMBERS ’ ~ 545 Technology Square Cambridge, MA 02139 11. CONTROLLING OFFICE NAME...AD-AI93 632 WMRT: A SECOND GENERTION MOBILE ROWT(U) / MASSACHUSETTS IMST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R BROOKS ET AL .JAN l8 Al-M...MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. Memo 1016 January, 1988 HERBERT: A SECOND GENERATION MOBILE ROBOT Rodney A

  11. 3D Object Recognition: Symmetry and Virtual Views

    DTIC Science & Technology

    1992-12-01

    NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial

  12. Artificial intelligence in the diagnosis of low back pain.

    PubMed

    Mann, N H; Brown, M D

    1991-04-01

    Computerized methods are used to recognize the characteristics of patient pain drawings. Artificial neural network (ANN) models are compared with expert predictions and traditional statistical classification methods when placing the pain drawings of low back pain patients into one of five clinically significant categories. A discussion is undertaken outlining the differences in these classifiers and the potential benefits of the ANN model as an artificial intelligence technique.

  13. Natural Object Categorization.

    DTIC Science & Technology

    1987-11-01

    6-A194 103 NATURAL OBJECT CATEGORIZATION(U) MASSACHUSETTS INST OF 1/3 TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB R F DBICK NOY 87 AI-TR-1091 NBSSI4...ORGANI1ZATION NAME AN40 ACORES$ 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA A WORK UNIT MUMBERS 545 Technology Square Cambridge...describes research done at the Department of Brain and Cognitive Sciences and the Artificial Intelligence Laboratory at the Massachusetts Institute of

  14. A quantum leap into the IED age

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

    Patterson, R.C.

    1996-11-01

    The integration of pattern recognition, artificial intelligence and advanced communication technologies in utility substation IED`s (Intelligent Electronic Devices) has opened the door to practical and cost effective automation of power distribution systems. A major driver for the application of these new technologies has been the research directed toward the detection of high-impedance faults. The commercial products which embody these complex detection functions have already expanded to include most of the protection, control, and monitoring required at a utility substation. These new Super-IED`s enable major utility initiatives, such as power quality management, improved public safety, operation and maintenance productivity, and powermore » system automation.« less

  15. Bayesian Networks in Educational Assessment

    PubMed Central

    Culbertson, Michael J.

    2015-01-01

    Bayesian networks (BN) provide a convenient and intuitive framework for specifying complex joint probability distributions and are thus well suited for modeling content domains of educational assessments at a diagnostic level. BN have been used extensively in the artificial intelligence community as student models for intelligent tutoring systems (ITS) but have received less attention among psychometricians. This critical review outlines the existing research on BN in educational assessment, providing an introduction to the ITS literature for the psychometric community, and points out several promising research paths. The online appendix lists 40 assessment systems that serve as empirical examples of the use of BN for educational assessment in a variety of domains. PMID:29881033

  16. Fundamental research in artificial intelligence at NASA

    NASA Technical Reports Server (NTRS)

    Friedland, Peter

    1990-01-01

    This paper describes basic research at NASA in the field of artificial intelligence. The work is conducted at the Ames Research Center and the Jet Propulsion Laboratory, primarily under the auspices of the NASA-wide Artificial Intelligence Program in the Office of Aeronautics, Exploration and Technology. The research is aimed at solving long-term NASA problems in missions operations, spacecraft autonomy, preservation of corporate knowledge about NASA missions and vehicles, and management/analysis of scientific and engineering data. From a scientific point of view, the research is broken into the categories of: planning and scheduling; machine learning; and design of and reasoning about large-scale physical systems.

  17. Real Estate Site Selection: An Application of Artificial Intelligence for Military Retail Facilities

    DTIC Science & Technology

    2006-09-01

    Information and Spatial Analysis (SCGISA), University of Sheffield. Kotler , P. (1984). Marketing Management: Analysis, Planning, and Control...Spatial Distribution of Retail Sales. Journal of Real Estate Finance and Economics, Vol. 31 Iss. 1, 53. Lilien, G., & Kotler , P. (1983). Marketing ...commissaries). The current business model for military retail facilities may not be optimized based upon current trends market data. Optimizing

  18. An Anticipatory and Deceptive AI Utilizing Bayesian Belief Networks

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

    Lake, Joe E; Allgood, Glenn O; Olama, Mohammed M

    The U.S. military defines antiterrorism as the defensive posture taken against terrorist threats. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, interdicting an event in progress, and ultimately mitigating and managing the consequences of an event. Recent events highlight the need for efficient tools for training our military and homeland security officers for anticipating threats posed by terrorists. These tools need to be easy enough so that they are readily usable without substantial training, but still maintain the complexity to allow for a level of deceptive reasoning on the part of themore » opponent. To meet this need, we propose to integrate a Bayesian Belief Network (BBN) model for threat anticipation and deceptive reasoning into training simulation environments currently utilized by several organizations within the Department of Defense (DoD). BBNs have the ability to deal with various types of uncertainties; such as identities, capabilities, target attractiveness, and the combinations of the previous. They also allow for disparate types of data to be fused in a coherent, analytically defensible, and understandable manner. A BBN has been developed by ORNL uses a network engineering process that treats the probability distributions of each node with in the broader context of the system development effort as a whole, and not in isolation. The network will be integrated into the Research Network Inc,(RNI) developed Game Distributed Interactive Simulation (GDIS) as a smart artificial intelligence module. GDIS is utilized by several DoD and civilian organizations as a distributed training tool for a multiplicity of reasons. It has garnered several awards for its realism, ease of use, and popularity. One area that it still has room to excel in, as most video training tools do, is in the area of artificial intelligence of opponent combatants. It is believed that by utilizing BBN as the backbone of the artificial intelligence code, a more realistic and helpful training experience will be available and enemy combatants that move and strategize with purpose will be obtained.« less

  19. Artificial Intelligence and Expert Systems Research and Their Possible Impact on Information Science.

    ERIC Educational Resources Information Center

    Borko, Harold

    1985-01-01

    Defines artificial intelligence (AI) and expert systems; describes library applications utilizing AI to automate creation of document representations, request formulations, and design and modify search strategies for information retrieval systems; discusses expert system development for information services; and reviews impact of these…

  20. Artificial Intelligence Applications to Videodisc Technology

    PubMed Central

    Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

    1985-01-01

    Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

  1. Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

    ERIC Educational Resources Information Center

    Moore, Gwendolyn B.; And Others

    1986-01-01

    Describes possible applications of new technologies to special education. Discusses results of a study designed to explore the use of robotics, artificial intelligence, and computer simulations to aid people with handicapping conditions. Presents several scenarios in which specific technological advances may contribute to special education…

  2. ICCE/ICCAI 2000 Full & Short Papers (Artificial Intelligence in Education).

    ERIC Educational Resources Information Center

    2000

    This document contains the full and short papers on artificial intelligence in education from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a computational model for learners' motivation states in individualized tutoring system; a…

  3. Soar: A Unified Theory of Cognition?

    ERIC Educational Resources Information Center

    Waldrop, M. Mitchell

    1988-01-01

    Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

  4. Artificial Intelligence: The Expert Way.

    ERIC Educational Resources Information Center

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  5. Artificial Intelligence in ADA: Pattern-Directed Processing. Final Report.

    ERIC Educational Resources Information Center

    Reeker, Larry H.; And Others

    To demonstrate to computer programmers that the programming language Ada provides superior facilities for use in artificial intelligence applications, the three papers included in this report investigate the capabilities that exist within Ada for "pattern-directed" programming. The first paper (Larry H. Reeker, Tulane University) is…

  6. Artificial Intelligence Is for Real: Undergraduate Students Should Know about It.

    ERIC Educational Resources Information Center

    Liebowitz, Jay

    1988-01-01

    Discussion of the possibilities of introducing artificial intelligence (AI) into the undergraduate curriculum highlights the introduction of AI in an introduction to information processing course for business students at George Washington University. Topics discussed include robotics, expert systems prototyping in class, and the interdisciplinary…

  7. Progress in cybernetics and systems research. Vol. XI. Data base design. International Information Systems. Semiotic Systems. Artificial Intelligence. Cybernetics and Philosophy. Special aspects

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

    Trappl, R.; Findler, N.V.; Horn, W.

    1982-01-01

    This book covers current research topics in six areas. These are data base design, international information systems, semiotic systems, artificial intelligence, cybernetics and philosophy, and special aspects of systems research. 1326 references.

  8. Artificial Intelligence: Applications in Education.

    ERIC Educational Resources Information Center

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  9. Development of the CODER System: A Testbed for Artificial Intelligence Methods in Information Retrieval.

    ERIC Educational Resources Information Center

    Fox, Edward A.

    1987-01-01

    Discusses the CODER system, which was developed to investigate the application of artificial intelligence methods to increase the effectiveness of information retrieval systems, particularly those involving heterogeneous documents. Highlights include the use of PROLOG programing, blackboard-based designs, knowledge engineering, lexicological…

  10. Automatic food detection in egocentric images using artificial intelligence technology

    USDA-ARS?s Scientific Manuscript database

    Our objective was to develop an artificial intelligence (AI)-based algorithm which can automatically detect food items from images acquired by an egocentric wearable camera for dietary assessment. To study human diet and lifestyle, large sets of egocentric images were acquired using a wearable devic...

  11. Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer.

    PubMed

    Ichimasa, Katsuro; Kudo, Shin-Ei; Mori, Yuichi; Misawa, Masashi; Matsudaira, Shingo; Kouyama, Yuta; Baba, Toshiyuki; Hidaka, Eiji; Wakamura, Kunihiko; Hayashi, Takemasa; Kudo, Toyoki; Ishigaki, Tomoyuki; Yagawa, Yusuke; Nakamura, Hiroki; Takeda, Kenichi; Haji, Amyn; Hamatani, Shigeharu; Mori, Kensaku; Ishida, Fumio; Miyachi, Hideyuki

    2018-03-01

     Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificial intelligence can predict LNM presence, thus minimizing the need for additional surgery.  Data on 690 consecutive patients with T1 CRCs that were surgically resected in 2001 - 2016 were retrospectively analyzed. We divided patients into two groups according to date: data from 590 patients were used for machine learning for the artificial intelligence model, and the remaining 100 patients were included for model validation. The artificial intelligence model analyzed 45 clinicopathological factors and then predicted positivity or negativity for LNM. Operative specimens were used as the gold standard for the presence of LNM. The artificial intelligence model was validated by calculating the sensitivity, specificity, and accuracy for predicting LNM, and comparing these data with those of the American, European, and Japanese guidelines.  Sensitivity was 100 % (95 % confidence interval [CI] 72 % to 100 %) in all models. Specificity of the artificial intelligence model and the American, European, and Japanese guidelines was 66 % (95 %CI 56 % to 76 %), 44 % (95 %CI 34 % to 55 %), 0 % (95 %CI 0 % to 3 %), and 0 % (95 %CI 0 % to 3 %), respectively; and accuracy was 69 % (95 %CI 59 % to 78 %), 49 % (95 %CI 39 % to 59 %), 9 % (95 %CI 4 % to 16 %), and 9 % (95 %CI 4 % - 16 %), respectively. The rates of unnecessary additional surgery attributable to misdiagnosing LNM-negative patients as having LNM were: 77 % (95 %CI 62 % to 89 %) for the artificial intelligence model, and 85 % (95 %CI 73 % to 93 %; P  < 0.001), 91 % (95 %CI 84 % to 96 %; P  < 0.001), and 91 % (95 %CI 84 % to 96 %; P  < 0.001) for the American, European, and Japanese guidelines, respectively.  Compared with current guidelines, artificial intelligence significantly reduced unnecessary additional surgery after endoscopic resection of T1 CRC without missing LNM positivity. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Human Factors Issues in the Use of Virtual and Augmented Reality for Military Purposes - USA

    DTIC Science & Technology

    2005-12-01

    and provide a means of output, MOVES has built a prototype system and continues research into the artificial intelligence and other factors required...role in any attempt to create automaton warriors. Indeed game-theoretic notions have been utilized in applications of artificial intelligence to...Review Board at the Defense Intelligence Agency (DIA). AFRL was notified that DIA will sponsor DTNG for Certification and Accreditation. Det 4 is expected

  13. Deductive Synthesis of the Unification Algorithm,

    DTIC Science & Technology

    1981-06-01

    DEDUCTIVE SYNTHESIS OF THE I - UNIFICATION ALGORITHM Zohar Manna Richard Waldinger I F? Computer Science Department Artificial Intelligence Center...theorem proving," Artificial Intelligence Journal, Vol. 9, No. 1, pp. 1-35. Boyer, R. S. and J S. Moore [Jan. 19751, "Proving theorems about LISP...d’Intelligence Artificielle , U.E.R. de Luminy, Universit6 d’ Aix-Marseille II. Green, C. C. [May 1969], "Application of theorem proving to problem

  14. Report on Ada (Trademark) Program Libraries Workshop Held at Monterey, California on November 1-3, 1983,

    DTIC Science & Technology

    1983-11-03

    capability. An intelligent library management system will be supported by knowledge-based techniques. In fact, until a formal specification of library...from artificial intelligence and information science 2 might also be useful, for example automatic indexing and cataloging schemes, methods for fast...Artificial Intelligence 5:1045-1058, 1977. [Burstall & Goguen 801 Burstall, R. M., and Goguen, J. A. The Semantics of Clear, a Specification Language. In

  15. Automated Test Requirement Document Generation

    DTIC Science & Technology

    1987-11-01

    DIAGNOSTICS BASED ON THE PRINCIPLES OF ARTIFICIAL INTELIGENCE ", 1984 International Test Conference, 01Oct84, (A3, 3, Cs D3, E2, G2, H2, 13, J6, K) 425...j0O GLOSSARY OF ACRONYMS 0 ABBREVIATION DEFINITION AFSATCOM Air Force Satellite Communication Al Artificial Intelligence ASIC Application Specific...In-Test Equipment (BITE) and AI ( Artificial Intelligence) - Expert Systems - need to be fully applied before a completely automated process can be

  16. Reification without Evaluation.

    DTIC Science & Technology

    1988-06-01

    PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UNIT NuMBERS ’’ 545 Technology Square 0 Cambridge, MA 02139 L $I 1, CONTROLLINO OFFICE NAME...7RD-ft" 28 REIFICRIO WITHOUT EYRURTION(U) rASSACHUSETTS INST OF 1/:LTECH CUZDGE ARTIFICI L INTELLIGENCE LUN R MEN JUN 60 RI-M-946 NM14-5-K-0-0124...themselves. This report, describes research done at, tie Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the

  17. Construction of Optimal-Path Maps for Homogeneous-Cost-Region Path-Planning Problems

    DTIC Science & Technology

    1989-09-01

    of Artificial Inteligence , 9%,4. 24. Kirkpatrick, S., Gelatt Jr., C. D., and Vecchi, M. P., "Optinization by Sinmulated Ani- nealing", Science, Vol...studied in depth by researchers in such fields as artificial intelligence, robot;cs, and computa- tional geometry. Most methods require homogeneous...the results of the research. 10 U. L SLEVANT RESEARCH A. APPLICABLE CONCEPTS FROM ARTIFICIAL INTELLIGENCE 1. Search Methods One of the central

  18. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    NASA Technical Reports Server (NTRS)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  19. Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

    DOE PAGES

    Stracuzzi, David J.; Gunning, David

    2015-09-28

    This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

  20. AI in CALL--Artificially Inflated or Almost Imminent?

    ERIC Educational Resources Information Center

    Schulze, Mathias

    2008-01-01

    The application of techniques from artificial intelligence (AI) to CALL has commonly been referred to as intelligent CALL (ICALL). ICALL is only slightly older than the "CALICO Journal", and this paper looks back at a quarter century of published research mainly in North America and by North American scholars. This "inventory…

  1. Robotics, Artificial Intelligence, Computer Simulation: Future Applications in Special Education.

    ERIC Educational Resources Information Center

    Moore, Gwendolyn B.; And Others

    The report describes three advanced technologies--robotics, artificial intelligence, and computer simulation--and identifies the ways in which they might contribute to special education. A hybrid methodology was employed to identify existing technology and forecast future needs. Following this framework, each of the technologies is defined,…

  2. Artificial Intelligence in Business: Technocrat Jargon or Quantum Leap?

    ERIC Educational Resources Information Center

    Burford, Anna M.; Wilson, Harold O.

    This paper addresses the characteristics and applications of artificial intelligence (AI) as a subsection of computer science, and briefly describes the most common types of AI programs: expert systems, natural language, and neural networks. Following a brief presentation of the historical background, the discussion turns to an explanation of how…

  3. Command History for 1990

    DTIC Science & Technology

    1991-05-01

    Marine Corps Tiaining Systems (CBESS) memorization training Inteligence Center, Dam Neck Threat memorization training Commander Tactical Wings, Atlantic...News Shipbuilding Technical training AEGIS Training Center, Dare Artificial Intelligence (Al) Tools Computerized firm-end analysis tools NETSCPAC...Technology Department and provides computational and electronic mail support for research in areas of artificial intelligence, computer-assisted instruction

  4. Magical Stories: Blending Virtual Reality and Artificial Intelligence.

    ERIC Educational Resources Information Center

    McLellan, Hilary

    Artificial intelligence (AI) techniques and virtual reality (VR) make possible powerful interactive stories, and this paper focuses on examples of virtual characters in three dimensional (3-D) worlds. Waldern, a virtual reality game designer, has theorized about and implemented software design of virtual teammates and opponents that incorporate AI…

  5. Introduction to the Special Issue on Innovative Applications of Artificial Intelligence 2014

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

    Stracuzzi, David J.; Gunning, David

    This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.

  6. RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

    EPA Science Inventory

    The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

  7. Artificial Intelligence and School Library Media Centers.

    ERIC Educational Resources Information Center

    Young, Robert J.

    1990-01-01

    Discusses developments in artificial intelligence in terms of their impact on school library media centers and the role of media specialists. Possible uses of expert systems, hypertext, and CD-ROM technologies in school media centers are examined and the challenges presented by these technologies are discussed. Fourteen sources of additional…

  8. Artificial Intelligence and the High School Computer Curriculum.

    ERIC Educational Resources Information Center

    Dillon, Richard W.

    1993-01-01

    Describes a four-part curriculum that can serve as a model for incorporating artificial intelligence (AI) into the high school computer curriculum. The model includes examining questions fundamental to AI, creating and designing an expert system, language processing, and creating programs that integrate machine vision with robotics and…

  9. Artificial Intelligence Applications in Special Education: How Feasible? Final Report.

    ERIC Educational Resources Information Center

    Hofmeister, Alan M.; Ferrara, Joseph M.

    The research project investigated whether expert system tools have become sophisticated enough to be applied efficiently to problems in special education. (Expert systems are a development of artificial intelligence that combines the computer's capacity for storing specialized knowledge with a general set of rules intended to replicate the…

  10. Artificial Intelligence Methods in Computer-Based Instructional Design. The Minnesota Adaptive Instructional System.

    ERIC Educational Resources Information Center

    Tennyson, Robert

    1984-01-01

    Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…

  11. Research and applications: Artificial intelligence

    NASA Technical Reports Server (NTRS)

    Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

    1970-01-01

    The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

  12. Artificial intelligence within AFSC

    NASA Technical Reports Server (NTRS)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  13. An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

    ERIC Educational Resources Information Center

    McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

    2016-01-01

    Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

  14. Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

    NASA Technical Reports Server (NTRS)

    Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

    1995-01-01

    This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system.

  15. LOGO Progress Report 1973-1975. Artificial Intelligence Memo Number 356. Revised.

    ERIC Educational Resources Information Center

    Abelson, H.; And Others

    This report outlines the accomplishments of the LOGO project of the Massachusetts Institute of Technology's Artificial Intelligence Laboratory during the period 1973-1975. Three major areas of work are listed: (1) building learning environments, (2) the theory behind the environments, and (3) experimenting with learning environments. Advances in…

  16. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

    PubMed Central

    Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

    2015-01-01

    In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced. PMID:26690164

  17. A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

    PubMed

    Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

    2015-12-04

    In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

  18. Artificial Intelligence and Its Use in Cost Type analyses with an Example in Cost Performance Measurement.

    DTIC Science & Technology

    1985-01-01

    7-Ai6i 817 ARTIFICIAL INTELLIGENCE AND ITS USE IN COST TYE1/I ANALYSES WdITH ANt EXAMPLE IN COST PERFORMANCE I MERSUREMENT(U) DEFENSE SYSTEMS...INTELLIGENCE-THE EMERGING TECHNOLOGY/ NATURAL LANGUAGE PROCESSORS K ~ With the advent of ARTIFICAL INTELLEGENCE (AI), we are entering into a new era of...language processor which is commerically available is INTELLECT, by Artifical Intellegence Incorporated, Waltham, Mass. To illustrate what a natural

  19. Mechanical Transformation of Task Heuristics into Operational Procedures

    DTIC Science & Technology

    1981-04-14

    Introduction A central theme of recent research in artificial intelligence is that *Intelligent task performance requires large amounts of knowledge...PLAY P1 C4] (. (LEADING (QSO)) (OR (CAN-LEAO- HEARrS (gSO)J (mEg (SUIT-OF C3) H])] C-) (FOLLOWING (QSO)) (OR [VOID (OSO) (SUIT-LED)3 [IN-SUIT C3 (SUIT...Production rules as a representation for a knowledge based consultation system. Artificial Intelligence 8:15-45, Spring, 1977. [Davis 77b] R. Davis

  20. Coupling artificial intelligence and numerical computation for engineering design (Invited paper)

    NASA Astrophysics Data System (ADS)

    Tong, S. S.

    1986-01-01

    The possibility of combining artificial intelligence (AI) systems and numerical computation methods for engineering designs is considered. Attention is given to three possible areas of application involving fan design, controlled vortex design of turbine stage blade angles, and preliminary design of turbine cascade profiles. Among the AI techniques discussed are: knowledge-based systems; intelligent search; and pattern recognition systems. The potential cost and performance advantages of an AI-based design-generation system are discussed in detail.

  1. Artificial intelligence (AI) systems for interpreting complex medical datasets.

    PubMed

    Altman, R B

    2017-05-01

    Advances in machine intelligence have created powerful capabilities in algorithms that find hidden patterns in data, classify objects based on their measured characteristics, and associate similar patients/diseases/drugs based on common features. However, artificial intelligence (AI) applications in medical data have several technical challenges: complex and heterogeneous datasets, noisy medical datasets, and explaining their output to users. There are also social challenges related to intellectual property, data provenance, regulatory issues, economics, and liability. © 2017 ASCPT.

  2. Artificial Intelligence in Maintenance: Proceedings of the Joint Services Workshop Held at Boulder, Colorado on 4-6 October 1983.

    DTIC Science & Technology

    1984-06-01

    intelligence . I strongly suspect that we’ll use data links to Rome so we can take advantage of both of the computer systems. Again, we see the need for close... data base indexing system would come up with a hit on those three key words I’ve just said. What is it? The hit is "artificial intelligence ." (This...pieces of data and is not classificatory in nature. In MDX there is S an intelligent data base component, called PATREC [6, 7], for doing such reasoning

  3. Faith in the algorithm, part 1: beyond the turing test

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

    Rodriguez, Marko A; Pepe, Alberto

    2009-01-01

    Since the Turing test was first proposed by Alan Turing in 1950, the goal of artificial intelligence has been predicated on the ability for computers to imitate human intelligence. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution. Another definition for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification, where the algorithms that are best at accomplishing this are deemed the most intelligent. This article surveys variousmore » systems that augment human and social intelligence.« less

  4. The dynamic lift of developmental process.

    PubMed

    Smith, Linda B; Breazeal, Cynthia

    2007-01-01

    What are the essential properties of human intelligence, currently unparalleled in its power relative to other biological forms and relative to artificial forms of intelligence? We suggest that answering this question depends critically on understanding developmental process. This paper considers three principles potentially essential to building human-like intelligence: the heterogeneity of the component processes, the embedding of development in a social world, and developmental processes that change the cognitive system as a function of the history of soft-assemblies of these heterogeneous processes in specific tasks. The paper uses examples from human development and from developmental robotics to show how these processes also may underlie biological intelligence and enable us to generate more advanced forms of artificial intelligence.

  5. Collective intelligence of the artificial life community on its own successes, failures, and future.

    PubMed

    Rasmussen, Steen; Raven, Michael J; Keating, Gordon N; Bedau, Mark A

    2003-01-01

    We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.

  6. Artificial intelligence in medicine: the challenges ahead.

    PubMed

    Coiera, E W

    1996-01-01

    The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the best computer scientists, and their work represents a remarkable achievement. However, AIM has not been successful-if success is judged as making an impact on the practice of medicine. Much recent work in AIM has been focused inward, addressing problems that are at the crossroads of the parent disciplines of medicine and artificial intelligence. Now, AIM must move forward with the insights that it has gained and focus on finding solutions for problems at the heart of medical practice. The growing emphasis within medicine on evidence-based practice should provide the right environment for that change.

  7. Analysis of the frontier technology of agricultural IoT and its predication research

    NASA Astrophysics Data System (ADS)

    Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Shen, Chen; Kong, Fantao

    2017-09-01

    Agricultural IoT (Internet of Things) develops rapidly. Nanotechnology, biotechnology and optoelectronic technology are successfully integrated into the agricultural sensor technology. Big data, cloud computing and artificial intelligence technology have also been successfully used in IoT. This paper carries out the research on integration of agricultural sensor technology, nanotechnology, biotechnology and optoelectronic technology and the application of big data, cloud computing and artificial intelligence technology in agricultural IoT. The advantages and development of the integration of nanotechnology, biotechnology and optoelectronic technology with agricultural sensor technology were discussed. The application of big data, cloud computing and artificial intelligence technology in IoT and their development trend were analysed.

  8. Utilization of artificial intelligence techniques for the Space Station power system

    NASA Technical Reports Server (NTRS)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  9. Structural analysis of peptides that fill sites near the active center of the two different enzyme molecules by artificial intelligence and computer simulations

    NASA Astrophysics Data System (ADS)

    Nishiyama, Katsuhiko

    2018-05-01

    Using artificial intelligence, the binding styles of 167 tetrapeptides were predicted in the active site of papain and cathepsin K. Five tetrapeptides (Asn-Leu-Lys-Trp, Asp-Gln-Trp-Gly, Cys-Gln-Leu-Arg, Gln-Leu-Trp-Thr and Arg-Ser-Glu-Arg) were found to bind sites near the active center of both papain and cathepsin K. These five tetrapeptides have the potential to also bind sites of other cysteine proteases, and structural characteristics of these tetrapeptides should aid the design of a common inhibitor of cysteine proteases. Smart application of artificial intelligence should accelerate data mining of important complex systems.

  10. Inspection Methods in Programming: Cliches and Plans.

    DTIC Science & Technology

    1987-12-01

    PROGRAM ELEMENT. PROJECT. TASK Artificial Inteligence Laboratory AREA & WORK UN IT NUMBERS J 545 Technology Square Cambridge, MA 02139 $L. CONTROLLING...U) MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB C RICH DEC 87 AI-M-±05 UNCLASSIFIED NW014-B5-K-0124 F/G 12/5 NL ’lllll l l l...S %P W. J % % %s MASSACHUSETTS INSTITUTE OF TECHNOLOGY N ARTIFICIAL INTELLIGENCE LABORATORY 00 A.I. Memo No. 1005 December 1987 N Inspection Methods

  11. Planning and Problem Solving

    DTIC Science & Technology

    1982-10-01

    Artificial Intelig ~ence (Vol. III, edited by Paul R. Cohen and’ Edward A.. Feigenbaum)’, The chapter was written B’ Paul Cohen, with contributions... Artificial Intelligence (Vol. III, edited by Paul R. Cohen and EdWard A. Feigenbaum). The chapter was written by Paul R. Cohen, with contributions by Stephen...Wheevoats"EntermdI’ Planning and Problem ’Solving by Paul R. Cohen Chaptb-rXV-of Volumec III’of the Handbook of Artificial Intelligence edited by Paul R

  12. Survey of Artificial Intelligence and Expert Systems in Library and Information Science Literature.

    ERIC Educational Resources Information Center

    Hsieh, Cynthia C.; Hall, Wendy

    1989-01-01

    Examines the definition and history of artificial intelligence (AI) and investigates the body of literature on AI found in "Library Literature" and "Library and Information Science Abstracts." The results reported include the number of articles by year and per journal, and the percentage of articles dealing with library…

  13. Artificial Intelligence Applications to Learning and Training. Occasional Paper--InTER/2/88.

    ERIC Educational Resources Information Center

    Cumming, Geoff

    This report summarizes and interprets the discussions at a seminar on artificial intelligence (AI) training domains and knowledge representations which was sponsored by the United Kingdom Training Commission. The following broad areas are addressed: (1) the context, process, and diversity of requirements of training and training needs; (2)…

  14. Artificial Intelligence, Counseling, and Cognitive Psychology.

    ERIC Educational Resources Information Center

    Brack, Greg; And Others

    With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

  15. Artificial Intelligence: Themes in the Second Decade. Memo Number 67.

    ERIC Educational Resources Information Center

    Feigenbaum, Edward A.

    The text of an invited address on artificial intelligence (AI) research over the 1963-1968 period is presented. A survey of recent studies on the computer simulation of intellective processes emphasizes developments in heuristic programing, problem-solving and closely related learning models. Progress and problems in these areas are indicated by…

  16. Simulated Classrooms and Artificial Students: The Potential Effects of New Technologies on Teacher Education.

    ERIC Educational Resources Information Center

    Brown, Abbie Howard

    1999-01-01

    Describes and discusses how simulation activities can be used in teacher education to augment the traditional field-experience approach, focusing on artificial intelligence, virtual reality, and intelligent tutoring systems. Includes an overview of simulation as a teaching and learning strategy and specific examples of high-technology simulations…

  17. Implications of Artificial Intelligence for End User Use of Online Systems.

    ERIC Educational Resources Information Center

    Smith, Linda C.

    1980-01-01

    Reviewed are several studies which demonstrate how artificial intelligence techniques can be applied in the design of end user-oriented interfaces (which would eliminate the need for an intermediary) to existing online systems, as well as in the development of future generations of online systems intended for the end user. (Author/SW)

  18. Turtle Escapes the Plane: Some Advanced Turtle Geometry. Artificial Intelligence Memo Number 348.

    ERIC Educational Resources Information Center

    diSessa, Andy

    The LOGO Turtles, originally developed at the Massachusetts Institute of Technology Artificial Intelligence Laboratory for teaching concepts in elementary geometry to primary-age children, can also be used in teaching higher-level mathematics. In the exercises described here, the turtle was programed to traverse curved surfaces. Both geometric and…

  19. Application of artificial intelligence to risk analysis for forested ecosystems

    Treesearch

    Daniel L. Schmoldt

    2001-01-01

    Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

  20. Exploiting Artificial Intelligence To Enhance Training: A Short- and Medium-Term Perspective.

    ERIC Educational Resources Information Center

    Cumming, Geoff

    This paper is an introductory discussion of industrial training, artificial intelligence (AI), and AI applications in training, prepared in the context of the United Kingdom Training Commission (TC) program. Following an outline of the activities and aims of the program, individual sections describe perspectives on: (1) training needs, including…

  1. A Retrospective and Prospective View of Information Retrieval and Artificial Intelligence in the 21st Century.

    ERIC Educational Resources Information Center

    Garfield, Eugene

    2001-01-01

    Traces the development of information retrieval/services and suggests that the creation of large digital libraries seems inevitable. Examines possibilities for increasing electronic access and the role of artificial intelligence. Highlights include: searching full text; sending full texts; selective dissemination of information (SDI) profiling and…

  2. Artificial Intelligence, Computational Thinking, and Mathematics Education

    ERIC Educational Resources Information Center

    Gadanidis, George

    2017-01-01

    Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…

  3. Automated Management Of Documents

    NASA Technical Reports Server (NTRS)

    Boy, Guy

    1995-01-01

    Report presents main technical issues involved in computer-integrated documentation. Problems associated with automation of management and maintenance of documents analyzed from perspectives of artificial intelligence and human factors. Technologies that may prove useful in computer-integrated documentation reviewed: these include conventional approaches to indexing and retrieval of information, use of hypertext, and knowledge-based artificial-intelligence systems.

  4. Artificial Intelligence Software Acquisition Program. Volume 2.

    DTIC Science & Technology

    1987-12-01

    34Architect tire prototyping in the software engineering environment". 1BBA! .’ qtins Jo urnal, vol. 23, No. 1, p. 4-18, 1984. 3v Boehmi, Barry W_. Gray...on Artificial Intelligence, Sponsored by AAAI, December 1986. ..- ~[31] Pressman , Roger S. "Software Engineering: A Practitioner’s Approach". McGraw

  5. An Artificial Intelligence Approach to the Symbolic Factorization of Multivariable Polynomials. Technical Report No. CS74019-R.

    ERIC Educational Resources Information Center

    Claybrook, Billy G.

    A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…

  6. Artificial Intelligence and Language Development and Language Usage with the Deaf.

    ERIC Educational Resources Information Center

    Leach, John Mark

    The paper reviews research on the application of artificial intelligence (AI) in language development and/or instruction with the deaf. Contributions of computer assisted instruction are noted, as are the problems resulting from over-dependence on a drill and practice format and from deaf students' difficulties in receiving and understanding new…

  7. Social Studies and Emerging Paradigms: Artificial Intelligence and Consciousness Education.

    ERIC Educational Resources Information Center

    Braun, Joseph A., Jr.

    1987-01-01

    Asks three questions: (1) Are machines capable of thinking as people do? (2) How is the thinking of computers similar and different from human thinking? and (3) What exactly is thinking? Examines research in artificial intelligence. Describes the theory and research of consciousness education and discusses an emerging paradigm for human thinking…

  8. Artificial Intelligence Applications to Fire Management

    Treesearch

    Don J. Latham

    1987-01-01

    Artificial intelligence could be used in Forest Service fire management and land-use planning to a larger degree than is now done. Robots, for example, could be programmed to monitor for fire and insect activity, to keep track of wildlife, and to do elementary thinking about the environment. Catching up with the fast-changing technology is imperative.

  9. The 1992 Goddard Conference on Space Applications of Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Rash, James L. (Editor)

    1992-01-01

    The purpose of this conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers fall into the following areas: planning and scheduling, control, fault monitoring/diagnosis and recovery, information management, tools, neural networks, and miscellaneous applications.

  10. Telerobot task planning and reasoning: Introduction to JPL artificial intelligence research

    NASA Technical Reports Server (NTRS)

    Atkinson, D. J.

    1987-01-01

    A view of the capabilities and areas of artificial intelligence research which are required for autonomous space telerobotics extending through the year 2000 is given. In the coming years, JPL will be conducting directed research to achieve these capabilities, as well as drawing heavily on collaborative efforts conducted with other research laboratories.

  11. Generative Computer-Assisted Instruction and Artificial Intelligence. Report No. 5.

    ERIC Educational Resources Information Center

    Sinnott, Loraine T.

    This paper reviews the state-of-the-art in generative computer-assisted instruction and artificial intelligence. It divides relevant research into three areas of instructional modeling: models of the subject matter; models of the learner's state of knowledge; and models of teaching strategies. Within these areas, work sponsored by Advanced…

  12. PROLOG to the Future: A Glimpse of Things to Come in Artificial Intelligence.

    ERIC Educational Resources Information Center

    Herther, Nancy K.

    1986-01-01

    Briefly introduces the programming languages of artificial intelligence and presents information on some of the new versions of these languages available for microcomputers. A tutorial for PROLOG-86, a new microcomputer version of PROLOG, is given. Information on other microcomputer versions of these programs and a bibliography are included.…

  13. Elements for an Ontology of Care in the Field of Artificial Intelligence.

    PubMed

    González Aguña, Alexandra; Fernández Batalla, Marta; Cercas Duque, Adriana; Herrero Jaén, Sara; Monsalvo San Macario, Enrique; Jiménez Rodríguez, Ma Lourdes; Santamaría García, José Ma; Ramírez Sánchez, Sylvia Claudine; Vialart Vidal, Niurka; Condor Camara, Daniel Flavio

    2018-01-01

    An ontology of care is a formal, explicit specification of a shared conceptualization. Constructing an ontology is a process that requires four elements: knowledge object, subject that knows, knowledge operation and result. These elements configure theframework to generate ontologies that can be used in Artificial Intelligence systems for care.

  14. An Artificial Intelligence-Based Distance Education System: Artimat

    ERIC Educational Resources Information Center

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  15. An Application of Fuzzy Analytic Hierarchy Process (FAHP) for Evaluating Students' Project

    ERIC Educational Resources Information Center

    Çebi, Ayça; Karal, Hasan

    2017-01-01

    In recent years, artificial intelligence applications for understanding the human thinking process and transferring it to virtual environments come into prominence. The fuzzy logic which paves the way for modeling human behaviors and expressing even vague concepts mathematically, and is also regarded as an artificial intelligence technique has…

  16. Massachusetts Institute of Technology Artificial Intelligence Laboratory Bibliography.

    ERIC Educational Resources Information Center

    Massachusetts Inst. of Tech., Cambridge. Artificial Intelligence Lab.

    Massachusetts Institute of Technology (MIT) presents a bibliography of more than 350 reports, theses, and papers from its artificial intelligence laboratory. Title, author, and identification number are given for all items, and most also have a date and contract number. Some items are no longer available, and others may be obtained from National…

  17. Prospects of second generation artificial intelligence tools in calibration of chemical sensors.

    PubMed

    Braibanti, Antonio; Rao, Rupenaguntla Sambasiva; Ramam, Veluri Anantha; Rao, Gollapalli Nageswara; Rao, Vaddadi Venkata Panakala

    2005-05-01

    Multivariate data driven calibration models with neural networks (NNs) are developed for binary (Cu++ and Ca++) and quaternary (K+, Ca++, NO3- and Cl-) ion-selective electrode (ISE) data. The response profiles of ISEs with concentrations are non-linear and sub-Nernstian. This task represents function approximation of multi-variate, multi-response, correlated, non-linear data with unknown noise structure i.e. multi-component calibration/prediction in chemometric parlance. Radial distribution function (RBF) and Fuzzy-ARTMAP-NN models implemented in the software packages, TRAJAN and Professional II, are employed for the calibration. The optimum NN models reported are based on residuals in concentration space. Being a data driven information technology, NN does not require a model, prior- or posterior- distribution of data or noise structure. Missing information, spikes or newer trends in different concentration ranges can be modeled through novelty detection. Two simulated data sets generated from mathematical functions are modeled as a function of number of data points and network parameters like number of neurons and nearest neighbors. The success of RBF and Fuzzy-ARTMAP-NNs to develop adequate calibration models for experimental data and function approximation models for more complex simulated data sets ensures AI2 (artificial intelligence, 2nd generation) as a promising technology in quantitation.

  18. Fifth Conference on Artificial Intelligence for Space Applications

    NASA Technical Reports Server (NTRS)

    Odell, Steve L. (Compiler)

    1990-01-01

    The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

  19. Experiments with microcomputer-based artificial intelligence environments

    USGS Publications Warehouse

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  20. Intelligent detection of cracks in metallic surfaces using a waveguide sensor loaded with metamaterial elements.

    PubMed

    Ali, Abdulbaset; Hu, Bing; Ramahi, Omar

    2015-05-15

    This work presents a real life experiment of implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impact in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks and the obtained experimental results showed good crack classification accuracy rates.

  1. Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

    NASA Astrophysics Data System (ADS)

    Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

    Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

  2. Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements

    PubMed Central

    Ali, Abdulbaset; Hu, Bing; Ramahi, Omar M.

    2015-01-01

    This work presents a real-life experiment implementing an artificial intelligence model for detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide sensor loaded with metamaterial elements. Crack detection using microwave sensors is typically based on human observation of change in the sensor's signal (pattern) depicted on a high-resolution screen of the test equipment. However, as demonstrated in this work, implementing artificial intelligence to classify cracked from non-cracked surfaces has appreciable impacts in terms of sensing sensitivity, cost, and automation. Furthermore, applying artificial intelligence for post-processing the data collected from microwave sensors is a cornerstone for handheld test equipment that can outperform rack equipment with large screens and sophisticated plotting features. The proposed method was tested on a metallic plate with different cracks, and the experimental results showed good crack classification accuracy rates. PMID:25988871

  3. Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

    PubMed

    Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

    2014-04-01

    This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Artificial Intelligence Based Selection of Optimal Cutting Tool and Process Parameters for Effective Turning and Milling Operations

    NASA Astrophysics Data System (ADS)

    Saranya, Kunaparaju; John Rozario Jegaraj, J.; Ramesh Kumar, Katta; Venkateshwara Rao, Ghanta

    2016-06-01

    With the increased trend in automation of modern manufacturing industry, the human intervention in routine, repetitive and data specific activities of manufacturing is greatly reduced. In this paper, an attempt has been made to reduce the human intervention in selection of optimal cutting tool and process parameters for metal cutting applications, using Artificial Intelligence techniques. Generally, the selection of appropriate cutting tool and parameters in metal cutting is carried out by experienced technician/cutting tool expert based on his knowledge base or extensive search from huge cutting tool database. The present proposed approach replaces the existing practice of physical search for tools from the databooks/tool catalogues with intelligent knowledge-based selection system. This system employs artificial intelligence based techniques such as artificial neural networks, fuzzy logic and genetic algorithm for decision making and optimization. This intelligence based optimal tool selection strategy is developed using Mathworks Matlab Version 7.11.0 and implemented. The cutting tool database was obtained from the tool catalogues of different tool manufacturers. This paper discusses in detail, the methodology and strategies employed for selection of appropriate cutting tool and optimization of process parameters based on multi-objective optimization criteria considering material removal rate, tool life and tool cost.

  5. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

    PubMed

    Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

    2018-04-01

    Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the clinical utility of the proposed sepsis prediction model.

  6. Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

    PubMed

    Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

    2004-02-01

    To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal hemorrhagic shock. We suggest that this technology may represent a noninvasive means of assessing the physiologic state during and immediately following hemorrhage. Point of care application of this technology may improve outcomes with earlier diagnosis and better titration of therapy of shock.

  7. Ortho Image and DTM Generation with Intelligent Methods

    NASA Astrophysics Data System (ADS)

    Bagheri, H.; Sadeghian, S.

    2013-10-01

    Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

  8. Software for Intelligent System Health Management

    NASA Technical Reports Server (NTRS)

    Trevino, Luis C.

    2004-01-01

    This viewgraph presentation describes the characteristics and advantages of autonomy and artificial intelligence in systems health monitoring. The presentation lists technologies relevant to Intelligent System Health Management (ISHM), and some potential applications.

  9. Autonomous power management and distribution

    NASA Technical Reports Server (NTRS)

    Dolce, Jim; Kish, Jim

    1990-01-01

    The goal of the Autonomous Power System program is to develop and apply intelligent problem solving and control to the Space Station Freedom's electric power testbed being developed at NASA's Lewis Research Center. Objectives are to establish artificial intelligence technology paths, craft knowledge-based tools and products for power systems, and integrate knowledge-based and conventional controllers. This program represents a joint effort between the Space Station and Office of Aeronautics and Space Technology to develop and demonstrate space electric power automation technology capable of: (1) detection and classification of system operating status, (2) diagnosis of failure causes, and (3) cooperative problem solving for power scheduling and failure recovery. Program details, status, and plans will be presented.

  10. An intelligent artificial throat with sound-sensing ability based on laser induced graphene

    PubMed Central

    Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

    2017-01-01

    Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas. PMID:28232739

  11. An intelligent artificial throat with sound-sensing ability based on laser induced graphene.

    PubMed

    Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

    2017-02-24

    Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas.

  12. Forecasting daily lake levels using artificial intelligence approaches

    NASA Astrophysics Data System (ADS)

    Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

    2012-04-01

    Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

  13. An intelligent artificial throat with sound-sensing ability based on laser induced graphene

    NASA Astrophysics Data System (ADS)

    Tao, Lu-Qi; Tian, He; Liu, Ying; Ju, Zhen-Yi; Pang, Yu; Chen, Yuan-Quan; Wang, Dan-Yang; Tian, Xiang-Guang; Yan, Jun-Chao; Deng, Ning-Qin; Yang, Yi; Ren, Tian-Ling

    2017-02-01

    Traditional sound sources and sound detectors are usually independent and discrete in the human hearing range. To minimize the device size and integrate it with wearable electronics, there is an urgent requirement of realizing the functional integration of generating and detecting sound in a single device. Here we show an intelligent laser-induced graphene artificial throat, which can not only generate sound but also detect sound in a single device. More importantly, the intelligent artificial throat will significantly assist for the disabled, because the simple throat vibrations such as hum, cough and scream with different intensity or frequency from a mute person can be detected and converted into controllable sounds. Furthermore, the laser-induced graphene artificial throat has the advantage of one-step fabrication, high efficiency, excellent flexibility and low cost, and it will open practical applications in voice control, wearable electronics and many other areas.

  14. A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

    NASA Astrophysics Data System (ADS)

    Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

    2016-03-01

    Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

  15. Edge Detection,

    DTIC Science & Technology

    1985-09-01

    PROJECT. T ASK0 Artificial Inteligence Laboratory AREA It WORK UNIT NUMBERS V 545 Technology Square ( Cambridge, HA 02139 I I* CONTOOL1LIN@4OFFICE NAME...ARD-A1t62 62 EDGE DETECTION(U) NASSACNUSETTS INST OF TECH CAMBRIDGE 1/1 ARTIFICIAL INTELLIGENCE LAB E C HILDRETH SEP 85 AI-M-8 N99SI4-8S-C-6595...used to carry out this analysis. cce~iO a N) ’.~" D LI’BL. P p ------------ Sj. t i MASSACHUSETTS INSTITUTE OF TECHNOLOGY i ARTIFICIAL INTELLIGENCE

  16. Autonomous power system brassboard

    NASA Technical Reports Server (NTRS)

    Merolla, Anthony

    1992-01-01

    The Autonomous Power System (APS) brassboard is a 20 kHz power distribution system which has been developed at NASA Lewis Research Center, Cleveland, Ohio. The brassboard exists to provide a realistic hardware platform capable of testing artificially intelligent (AI) software. The brassboard's power circuit topology is based upon a Power Distribution Control Unit (PDCU), which is a subset of an advanced development 20 kHz electrical power system (EPS) testbed, originally designed for Space Station Freedom (SSF). The APS program is designed to demonstrate the application of intelligent software as a fault detection, isolation, and recovery methodology for space power systems. This report discusses both the hardware and software elements used to construct the present configuration of the brassboard. The brassboard power components are described. These include the solid-state switches (herein referred to as switchgear), transformers, sources, and loads. Closely linked to this power portion of the brassboard is the first level of embedded control. Hardware used to implement this control and its associated software is discussed. An Ada software program, developed by Lewis Research Center's Space Station Freedom Directorate for their 20 kHz testbed, is used to control the brassboard's switchgear, as well as monitor key brassboard parameters through sensors located within these switches. The Ada code is downloaded from a PC/AT, and is resident within the 8086 microprocessor-based embedded controllers. The PC/AT is also used for smart terminal emulation, capable of controlling the switchgear as well as displaying data from them. Intelligent control is provided through use of a T1 Explorer and the Autonomous Power Expert (APEX) LISP software. Real-time load scheduling is implemented through use of a 'C' program-based scheduling engine. The methods of communication between these computers and the brassboard are explored. In order to evaluate the features of both the brassboard hardware and intelligent controlling software, fault circuits have been developed and integrated as part of the brassboard. A description of these fault circuits and their function is included. The brassboard has become an extremely useful test facility, promoting artificial intelligence (AI) applications for power distribution systems. However, there are elements of the brassboard which could be enhanced, thus improving system performance. Modifications and enhancements to improve the brassboard's operation are discussed.

  17. The Evolution of Instructional Design Principles for Intelligent Computer-Assisted Instruction.

    ERIC Educational Resources Information Center

    Dede, Christopher; Swigger, Kathleen

    1988-01-01

    Discusses and compares the design and development of computer assisted instruction (CAI) and intelligent computer assisted instruction (ICAI). Topics discussed include instructional systems design (ISD), artificial intelligence, authoring languages, intelligent tutoring systems (ITS), qualitative models, and emerging issues in instructional…

  18. Selective Snapshot of State-of-the-Art Artificial Intelligence & Robotics with Reference to the Icarus Starship

    NASA Astrophysics Data System (ADS)

    Ellery, A.

    Since the remarkable British Interplanetary Society starship study of the late 1970s - Daedalus - there have been significant developments in the areas of artificial intelligence and robotics. These will be critical technologies for any starship as indeed they are for the current generation of exploratory spacecraft and in-situ planetary robotic explorers. Although early visions of truly intelligent robots have yet to materialize (reasons for which will be outlined), there are nonetheless revolutionary developments which have attempted to address at least some of these earlier unperceived deficiencies. The current state of the art comprises a number of separate strands of research which provide components of robotic intelligence though no over- arching approach has been forthcoming. The first question to be considered is the level of intelligent functionality required to support a long-duration starship mission. This will, at a minimum, need to be extensive imposed by the requirement for complex reconfigurability and repair. The second question concerns the tools that we have at our disposal to implement the required intelligent functions of the starship. These are based on two very different approaches - good old-fashioned artificial intelligence (GOFAI) based on logical theorem-proving and knowledge-encoding recently augmented by modal, temporal, circumscriptive and fuzzy logics to address the well-known “frame problem”; and the more recent soft computing approaches based on artificial neural networks, evolutionary algorithms and immunity models and their variants to implement learning. The former has some flight heritage through the Remote Agent architecture whilst the latter has yet to be deployed on any space mission. However, the notion of reconfigurable hardware of recent interest in the space community warrants the use of evolutionary algorithms and neural networks implemented on field programmable gate array technology, blurring the distinction between hardware and software. The primary question in space engineering has traditionally been one of predictability and controllability which online learning compromises. A further factor to be accounted for is the notion that intelligence is derived primarily from robot-environment interaction which stresses the sensory and actuation capabilities (exemplified by the behavioural or situated robotics paradigm). One major concern is whether the major deficiency of current methods in terms of lack of scalability can be overcome using a highly distributed approach rather than the hierarchical approach suggested by the NASREM architecture. It is contended here that a mixed solution will be required where a priori programming is augmented by a posteriori learning resembling the biological distinction between fixed genetically inherited and learned neurally implemented behaviour in animals. In particular, a biomimetic approach is proferred which exploits the neural processes and architecture of the human brain through the use of forward models which attempts to marry the conflicting requirements of learning with predictability. Some small-scale efforts in this direction will be outlined.

  19. The Reliability Estimation for the Open Function of Cabin Door Affected by the Imprecise Judgment Corresponding to Distribution Hypothesis

    NASA Astrophysics Data System (ADS)

    Yu, Z. P.; Yue, Z. F.; Liu, W.

    2018-05-01

    With the development of artificial intelligence, more and more reliability experts have noticed the roles of subjective information in the reliability design of complex system. Therefore, based on the certain numbers of experiment data and expert judgments, we have divided the reliability estimation based on distribution hypothesis into cognition process and reliability calculation. Consequently, for an illustration of this modification, we have taken the information fusion based on intuitional fuzzy belief functions as the diagnosis model of cognition process, and finished the reliability estimation for the open function of cabin door affected by the imprecise judgment corresponding to distribution hypothesis.

  20. Social Media: Menagerie of Metrics

    DTIC Science & Technology

    2010-01-27

    intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm . An EA...Cloning - 22 Animals were cloned to date; genetic algorithms can help prediction (e.g. “elitism” - attempts to ensure selection by including performers...28, 2010 Evolutionary Algorithm • Evolutionary algorithm From Wikipedia, the free encyclopedia Artificial intelligence portal In artificial

  1. Artificial Intelligence in Education--State of the Art and Perspectives. ZIFF Papiere 111.

    ERIC Educational Resources Information Center

    Buiu, Catalin

    This review contains an overview of past and present trends in the application of what is called "artificial intelligence" in traditional face-to-face education and in distance education. The reviewed trends are illustrated with examples of research projects and results throughout the world. The first section of the review discusses intelligence…

  2. Data mining: sophisticated forms of managed care modeling through artificial intelligence.

    PubMed

    Borok, L S

    1997-01-01

    Data mining is a recent development in computer science that combines artificial intelligence algorithms and relational databases to discover patterns automatically, without the use of traditional statistical methods. Work with data mining tools in health care is in a developmental stage that holds great promise, given the combination of demographic and diagnostic information.

  3. Evolution and Revolution in Artificial Intelligence in Education

    ERIC Educational Resources Information Center

    Roll, Ido; Wylie, Ruth

    2016-01-01

    The field of Artificial Intelligence in Education (AIED) has undergone significant developments over the last twenty-five years. As we reflect on our past and shape our future, we ask two main questions: What are our major strengths? And, what new opportunities lay on the horizon? We analyse 47 papers from three years in the history of the…

  4. Second Conference on Artificial Intelligence for Space Applications

    NASA Technical Reports Server (NTRS)

    Dollman, Thomas (Compiler)

    1988-01-01

    The proceedings of the conference are presented. This second conference on Artificial Intelligence for Space Applications brings together a diversity of scientific and engineering work and is intended to provide an opportunity for those who employ AI methods in space applications to identify common goals and to discuss issues of general interest in the AI community.

  5. New directions for Artificial Intelligence (AI) methods in optimum design

    NASA Technical Reports Server (NTRS)

    Hajela, Prabhat

    1989-01-01

    Developments and applications of artificial intelligence (AI) methods in the design of structural systems is reviewed. Principal shortcomings in the current approach are emphasized, and the need for some degree of formalism in the development environment for such design tools is underscored. Emphasis is placed on efforts to integrate algorithmic computations in expert systems.

  6. AI at Ames: Artificial Intelligence research and application at NASA Ames Research Center, Moffett Field, California, February 1985

    NASA Technical Reports Server (NTRS)

    Andrews, Alison E. (Editor)

    1985-01-01

    Charts are given that illustrate function versus domain for artificial intelligence (AI) applications and interests and research area versus project number for AI research. A list is given of project titles with associated project numbers and page numbers. Also, project descriptions, including title, participants, and status are given.

  7. Fuzzy Logic, Neural Networks, Genetic Algorithms: Views of Three Artificial Intelligence Concepts Used in Modeling Scientific Systems

    ERIC Educational Resources Information Center

    Sunal, Cynthia Szymanski; Karr, Charles L.; Sunal, Dennis W.

    2003-01-01

    Students' conceptions of three major artificial intelligence concepts used in the modeling of systems in science, fuzzy logic, neural networks, and genetic algorithms were investigated before and after a higher education science course. Students initially explored their prior ideas related to the three concepts through active tasks. Then,…

  8. The Use of Artificial Neural Networks to Estimate Speech Intelligibility from Acoustic Variables: A Preliminary Analysis.

    ERIC Educational Resources Information Center

    Metz, Dale Evan; And Others

    1992-01-01

    A preliminary scheme for estimating the speech intelligibility of hearing-impaired speakers from acoustic parameters, using a computerized artificial neural network to process mathematically the acoustic input variables, is outlined. Tests with 60 hearing-impaired speakers found the scheme to be highly accurate in identifying speakers separated by…

  9. The Seeds of Artificial Intelligence. SUMEX-AIM.

    ERIC Educational Resources Information Center

    Research Resources Information Center, Rockville, MD.

    Written to provide an understanding of the broad base of information on which the artificial intelligence (AI) branch of computer science rests, this publication presents a general view of AI, the concepts from which it evolved, its current abilities, and its promise for research. The focus is on a community of projects that use the SUMEX-AIM…

  10. Artificial Intelligence, Expert Systems, Natural Language Interfaces, Knowledge Engineering and the Librarian.

    ERIC Educational Resources Information Center

    Davies, Jim

    This paper begins by examining concepts of artificial intelligence (AI) and discusses various definitions of the concept that have been suggested in the literature. The nesting relationship of expert systems within the broader framework of AI is described, and expert systems are characterized as knowledge-based systems (KBS) which attempt to solve…

  11. Applications of Artificial Intelligence (AI) and Expert Systems for Online Searching.

    ERIC Educational Resources Information Center

    Hawkins, Donald T.

    1988-01-01

    Discussion of the online searching process identifies the formulation of a search strategy as the major problem area for users of online systems. Artificial intelligence is suggested as a solution to this problem, and several expert systems for information retrieval are described. An annotated list of 24 items for further reading is included. (23…

  12. Developing Applications of Artificial Intelligence Technology To Provide Consultative Support in the Use of Research Methodology by Practitioners.

    ERIC Educational Resources Information Center

    Vitale, Michael R.; Romance, Nancy

    Adopting perspectives based on applications of artificial intelligence proven in industry, this paper discusses methodological strategies and issues that underlie the development of such software environments. The general concept of an expert system is discussed in the context of its relevance to the problem of increasing the accessibility of…

  13. Applications of artificial intelligence systems in the analysis of epidemiological data.

    PubMed

    Flouris, Andreas D; Duffy, Jack

    2006-01-01

    A brief review of the germane literature suggests that the use of artificial intelligence (AI) statistical algorithms in epidemiology has been limited. We discuss the advantages and disadvantages of using AI systems in large-scale sets of epidemiological data to extract inherent, formerly unidentified, and potentially valuable patterns that human-driven deductive models may miss.

  14. Keeping Pace with New Technology: An Introduction to Robotics, FORTH, and Artificial Intelligence.

    ERIC Educational Resources Information Center

    Reck, Gene

    A course was developed to introduce students at a community college to four major areas of emphasis in emerging technologies: FORTH programming language, elementary electronic theory, robotics, and artificial intelligence. After a needs assessment indicated the importance of such a course, a pretest focusing on the four areas was given to students…

  15. The Roles of Artificial Intelligence in Education: Current Progress and Future Prospects

    ERIC Educational Resources Information Center

    McArthur, David; Lewis, Matthew; Bishary, Miriam

    2005-01-01

    This report begins by summarizing current applications of ideas from artificial intelligence (Al) to education. It then uses that summary to project various future applications of Al--and advanced technology in general--to education, as well as highlighting problems that will confront the wide­ scale implementation of these technologies in the…

  16. Dynamic Restructuring Of Problems In Artificial Intelligence

    NASA Technical Reports Server (NTRS)

    Schwuttke, Ursula M.

    1992-01-01

    "Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

  17. The Effects of Textisms on Learning, Study Time, and Instructional Perceptions in an Online Artificial Intelligence Instructional Module

    ERIC Educational Resources Information Center

    Beasley, Robert; Bryant, Nathan L.; Dodson, Phillip T.; Entwistle, Kevin C.

    2013-01-01

    The purpose of this study was to investigate the effects of textisms (i.e., abbreviated spellings, acronyms, and other shorthand notations) on learning, study time, and instructional perceptions in an online artificial intelligence instructional module. The independent variable in this investigation was experimental condition. For the control…

  18. Artificial Intelligence: Is the Future Now for A.I.?

    ERIC Educational Resources Information Center

    Ramaswami, Rama

    2009-01-01

    In education, artificial intelligence (AI) has not made much headway. In the one area where it would seem poised to lend the most benefit--assessment--the reliance on standardized tests, intensified by the demands of the No Child Left Behind Act of 2001, which holds schools accountable for whether students pass statewide exams, precludes its use.…

  19. Games and machine learning: a powerful combination in an artificial intelligence course

    NASA Astrophysics Data System (ADS)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  20. Space Station Mission Planning System (MPS) development study. Volume 2

    NASA Technical Reports Server (NTRS)

    Klus, W. J.

    1987-01-01

    The process and existing software used for Spacelab payload mission planning were studied. A complete baseline definition of the Spacelab payload mission planning process was established, along with a definition of existing software capabilities for potential extrapolation to the Space Station. This information was used as a basis for defining system requirements to support Space Station mission planning. The Space Station mission planning concept was reviewed for the purpose of identifying areas where artificial intelligence concepts might offer substantially improved capability. Three specific artificial intelligence concepts were to be investigated for applicability: natural language interfaces; expert systems; and automatic programming. The advantages and disadvantages of interfacing an artificial intelligence language with existing FORTRAN programs or of converting totally to a new programming language were identified.

  1. Artificial intelligence in medicine: the challenges ahead.

    PubMed Central

    Coiera, E W

    1996-01-01

    The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the best computer scientists, and their work represents a remarkable achievement. However, AIM has not been successful-if success is judged as making an impact on the practice of medicine. Much recent work in AIM has been focused inward, addressing problems that are at the crossroads of the parent disciplines of medicine and artificial intelligence. Now, AIM must move forward with the insights that it has gained and focus on finding solutions for problems at the heart of medical practice. The growing emphasis within medicine on evidence-based practice should provide the right environment for that change. PMID:8930853

  2. [Detection of endpoint for segmentation between consonants and vowels in aphasia rehabilitation software based on artificial intelligence scheduling].

    PubMed

    Deng, Xingjuan; Chen, Ji; Shuai, Jie

    2009-08-01

    For the purpose of improving the efficiency of aphasia rehabilitation training, artificial intelligence-scheduling function is added in the aphasia rehabilitation software, and the software's performance is improved. With the characteristics of aphasia patient's voice as well as with the need of artificial intelligence-scheduling functions under consideration, the present authors have designed a set of endpoint detection algorithm. It determines the reference endpoints, then extracts every word and ensures the reasonable segmentation points between consonants and vowels, using the reference endpoints. The results of experiments show that the algorithm is able to attain the objects of detection at a higher accuracy rate. Therefore, it is applicable to the detection of endpoint on aphasia-patient's voice.

  3. The Successive Contributions of Computers to Education: A Survey.

    ERIC Educational Resources Information Center

    Lelouche, Ruddy

    1998-01-01

    Shows how education has successively benefited from traditional information processing through programmed instruction and computer-assisted instruction (CAI), artificial intelligence, intelligent CAI, intelligent tutoring systems, and hypermedia techniques. Contains 29 references. (DDR)

  4. Intelligent E-Learning Systems: Automatic Construction of Ontologies

    NASA Astrophysics Data System (ADS)

    Peso, Jesús del; de Arriaga, Fernando

    2008-05-01

    During the last years a new generation of Intelligent E-Learning Systems (ILS) has emerged with enhanced functionality due, mainly, to influences from Distributed Artificial Intelligence, to the use of cognitive modelling, to the extensive use of the Internet, and to new educational ideas such as the student-centered education and Knowledge Management. The automatic construction of ontologies provides means of automatically updating the knowledge bases of their respective ILS, and of increasing their interoperability and communication among them, sharing the same ontology. The paper presents a new approach, able to produce ontologies from a small number of documents such as those obtained from the Internet, without the assistance of large corpora, by using simple syntactic rules and some semantic information. The method is independent of the natural language used. The use of a multi-agent system increases the flexibility and capability of the method. Although the method can be easily improved, the results so far obtained, are promising.

  5. NASA/ARC proposed training in intelligent control

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1990-01-01

    Viewgraphs on NASA Ames Research Center proposed training in intelligent control was presented. Topics covered include: fuzzy logic control; neural networks in control; artificial intelligence in control; hybrid approaches; hands on experience; and fuzzy controllers.

  6. Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.

    PubMed

    Labovitz, Daniel L; Shafner, Laura; Reyes Gil, Morayma; Virmani, Deepti; Hanina, Adam

    2017-05-01

    This study evaluated the use of an artificial intelligence platform on mobile devices in measuring and increasing medication adherence in stroke patients on anticoagulation therapy. The introduction of direct oral anticoagulants, while reducing the need for monitoring, have also placed pressure on patients to self-manage. Suboptimal adherence goes undetected as routine laboratory tests are not reliable indicators of adherence, placing patients at increased risk of stroke and bleeding. A randomized, parallel-group, 12-week study was conducted in adults (n=28) with recently diagnosed ischemic stroke receiving any anticoagulation. Patients were randomized to daily monitoring by the artificial intelligence platform (intervention) or to no daily monitoring (control). The artificial intelligence application visually identified the patient, the medication, and the confirmed ingestion. Adherence was measured by pill counts and plasma sampling in both groups. For all patients (n=28), mean (SD) age was 57 years (13.2 years) and 53.6% were women. Mean (SD) cumulative adherence based on the artificial intelligence platform was 90.5% (7.5%). Plasma drug concentration levels indicated that adherence was 100% (15 of 15) and 50% (6 of 12) in the intervention and control groups, respectively. Patients, some with little experience using a smartphone, successfully used the technology and demonstrated a 50% improvement in adherence based on plasma drug concentration levels. For patients receiving direct oral anticoagulants, absolute improvement increased to 67%. Real-time monitoring has the potential to increase adherence and change behavior, particularly in patients on direct oral anticoagulant therapy. URL: http://www.clinicaltrials.gov. Unique identifier: NCT02599259. © 2017 American Heart Association, Inc.

  7. Artificial intelligence, neural network, and Internet tool integration in a pathology workstation to improve information access

    NASA Astrophysics Data System (ADS)

    Sargis, J. C.; Gray, W. A.

    1999-03-01

    The APWS allows user friendly access to several legacy systems which would normally each demand domain expertise for proper utilization. The generalized model, including objects, classes, strategies and patterns is presented. The core components of the APWS are the Microsoft Windows 95 Operating System, Oracle, Oracle Power Objects, Artificial Intelligence tools, a medical hyperlibrary and a web site. The paper includes a discussion of how could be automated by taking advantage of the expert system, object oriented programming and intelligent relational database tools within the APWS.

  8. Analysis of optoelectronic strategic planning in Taiwan by artificial intelligence portfolio tool

    NASA Astrophysics Data System (ADS)

    Chang, Rang-Seng

    1992-05-01

    Taiwan ROC has achieved significant advances in the optoelectronic industry with some Taiwan products ranked high in the world market and technology. Six segmentations of optoelectronic were planned. Each one was divided into several strategic items, design artificial intelligent portfolio tool (AIPT) to analyze the optoelectronic strategic planning in Taiwan. The portfolio is designed to provoke strategic thinking intelligently. This computer- generated strategy should be selected and modified by the individual. Some strategies for the development of the Taiwan optoelectronic industry also are discussed in this paper.

  9. Design of Distributed Cyber-Physical Systems for Connected and Automated Vehicles with Implementing Methodologies

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

    Feng, Yixiong; Hu, Bingtao; Hao, He

    With the development of communication and control technology, intelligent transportation systems have received increasing attention from both industry and academia. Intelligent transportation systems are supported by the Internet of Things, Cyber-Physical System, Artificial Intelligence, Cloud Computing and many other technologies, which supply fundamental information for connected and automated vehicles. Although plenty of studies have provided different formulations for intelligent transportation systems, many of them depend on Master Control Center. However, a centralized control mode requires a huge amount of data transmission and high level of hardware configuration and may cause communication delay and privacy leak. Some distributed architectures have beenmore » proposed to overcome the above problems but systematized technologies to collect and exchange information, process large amounts of data, model the dynamics of vehicles, and safely control the connected and automated vehicles are not explored in detail. In this paper, we proposed a novel distributed cyber-physical system for connected and automated vehicles in which every vehicle is modeled as a double-integrator using edge computing to analyze information collected from its nearest neighbors. The vehicles are supposed to travel along a desired trajectory and to maintain a rigid formation geometry. Related methodologies for the proposed system are illustrated and experiments are conducted showing that the performance of the connected and automated vehicles matches very well with analytic predictions. Some design guidelines and open questions are provided for the future study.« less

  10. Design of Distributed Cyber-Physical Systems for Connected and Automated Vehicles with Implementing Methodologies

    DOE PAGES

    Feng, Yixiong; Hu, Bingtao; Hao, He; ...

    2018-02-14

    With the development of communication and control technology, intelligent transportation systems have received increasing attention from both industry and academia. Intelligent transportation systems are supported by the Internet of Things, Cyber-Physical System, Artificial Intelligence, Cloud Computing and many other technologies, which supply fundamental information for connected and automated vehicles. Although plenty of studies have provided different formulations for intelligent transportation systems, many of them depend on Master Control Center. However, a centralized control mode requires a huge amount of data transmission and high level of hardware configuration and may cause communication delay and privacy leak. Some distributed architectures have beenmore » proposed to overcome the above problems but systematized technologies to collect and exchange information, process large amounts of data, model the dynamics of vehicles, and safely control the connected and automated vehicles are not explored in detail. In this paper, we proposed a novel distributed cyber-physical system for connected and automated vehicles in which every vehicle is modeled as a double-integrator using edge computing to analyze information collected from its nearest neighbors. The vehicles are supposed to travel along a desired trajectory and to maintain a rigid formation geometry. Related methodologies for the proposed system are illustrated and experiments are conducted showing that the performance of the connected and automated vehicles matches very well with analytic predictions. Some design guidelines and open questions are provided for the future study.« less

  11. Diverse Data Sets for Impact

    DTIC Science & Technology

    2018-02-01

    Defense Actions Against Test-Set Attacks”, In Proceedings of the Conference on Artificial Intelligence (AAAI), San Francisco, CA, February, 2017...Scott Alfeld, Jerry Zhu and Paul Barford. “Data Poisoning Attacks against Autoregressive Models”, In Proceedings of the Conference on Artificial ... Intelligence (AAAI), Phoenix, AZ, February, 2016. 7) Aaron Cahn, Scot Alfeld, Paul Barford and S. Muthukrishnan. “An Empirical Study of Web Cookies

  12. Reflections on the relationship between artificial intelligence and operations research

    NASA Technical Reports Server (NTRS)

    Fox, Mark S.

    1989-01-01

    Historically, part of Artificial Intelligence's (AI's) roots lie in Operations Research (OR). How AI has extended the problem solving paradigm developed in OR is explored. In particular, by examining how scheduling problems are solved using OR and AI, it is demonstrated that AI extends OR's model of problem solving through the opportunistic use of knowledge, problem reformulation and learning.

  13. The Use of Video Technology for the Fast-Prototyping of Artificially Intelligent Software.

    ERIC Educational Resources Information Center

    Klein, Gary L.

    This paper describes the use of video to provide a screenplay depiction of a proposed artificial intelligence software system. Advantages of such use are identified: (1) the video can be used to provide a clear conceptualization of the proposed system; (2) it can illustrate abstract technical concepts; (3) it can simulate the functions of the…

  14. Three Years of Using Robots in an Artificial Intelligence Course: Lessons Learned

    ERIC Educational Resources Information Center

    Kumar, Amruth N.

    2004-01-01

    We have been using robots in our artificial intelligence course since fall 2000. We have been using the robots for open-laboratory projects. The projects are designed to emphasize high-level knowledge-based AI algorithms. After three offerings of the course, we paused to analyze the collected data and to see if we could answer the following…

  15. Automatic Synthesis of Fine-Motion Strategies for Robots.

    DTIC Science & Technology

    1983-12-01

    ADA-A39 532 AUTOMATI CSYNTHESISOF FNE-MOTIONSTRATEGIESFORa R080 S(U) MASSACHUSETTS INS OF TECH CAMBRIDOE ARTIFCIAL INTELLGENCE LAB IOZANO-PEREZ DEC...N00014-82-K-0334 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA...provides correct- ness criteria for compliant motion strategies. MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY A. I. MEMO 759

  16. Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

    ERIC Educational Resources Information Center

    Sayre, Scott Alan

    The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

  17. Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

    DTIC Science & Technology

    1984-06-01

    other automatic machinery such as presses, molding machines , and numerically-controlled machine tools, just as people do. A-36...Robotics Technologies 3 B. Relevant AI Technologies 4 1. Expert Systems 4 2. Automatic Planning 4 3. Natural Language 5 4. Machine Vision...building machines that imitate human behavior. Artificial intelligence is concerned with the functions of the brain, whereas robotics include, in

  18. Artificial Intelligence Methods: Challenge in Computer Based Polymer Design

    NASA Astrophysics Data System (ADS)

    Rusu, Teodora; Pinteala, Mariana; Cartwright, Hugh

    2009-08-01

    This paper deals with the use of Artificial Intelligence Methods (AI) in the design of new molecules possessing desired physical, chemical and biological properties. This is an important and difficult problem in the chemical, material and pharmaceutical industries. Traditional methods involve a laborious and expensive trial-and-error procedure, but computer-assisted approaches offer many advantages in the automation of molecular design.

  19. Prediction of shipboard electromagnetic interference (EMI) problems using artificial intelligence (AI) technology

    NASA Technical Reports Server (NTRS)

    Swanson, David J.

    1990-01-01

    The electromagnetic interference prediction problem is characteristically ill-defined and complicated. Severe EMI problems are prevalent throughout the U.S. Navy, causing both expected and unexpected impacts on the operational performance of electronic combat systems onboard ships. This paper focuses on applying artificial intelligence (AI) technology to the prediction of ship related electromagnetic interference (EMI) problems.

  20. Deducing the multi-trader population driving a financial market

    NASA Astrophysics Data System (ADS)

    Gupta, Nachi; Hauser, Raphael; Johnson, Neil

    2005-12-01

    We have previously laid out a basic framework for predicting financial movements and pockets of predictability by tracking the distribution of a multi-trader population playing on an artificial financial market model. This work explores extensions to this basic framework. We allow for more intelligent agents with a richer strategy set, and we no longer constrain the distribution over these agents to a probability space. We then introduce a fusion scheme which accounts for multiple runs of randomly chosen sets of possible agent types. We also discuss a mechanism for bias removal on the estimates.

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