Distributed Artificial Intelligence

Distributed Artificial Intelligence

by Michael N. Huhns
Released December 2012
Publisher(s): Morgan Kaufmann
ISBN: 9780323137591

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Book description

Distributed Artificial Intelligence presents a collection of papers describing the state of research in distributed artificial intelligence (DAI). DAI is concerned with the cooperative solution of problems by a decentralized group of agents. The agents may range from simple processing elements to complex entities exhibiting rational behavior.

The book is organized into three parts. Part I addresses ways to develop control abstractions that efficiently guide problem-solving; communication abstractions that yield cooperation; and description abstractions that result in effective organizational structure. Part II describes architectures for developing and testing DAI systems. Part III discusses applications of DAI in manufacturing, office automation, and man-machine interactions.

This book is intended for researchers, system developers, and students in artificial intelligence and related disciplines. It can also be used as a reference for students and researchers in other disciplines, such as psychology, philosophy, robotics, and distributed computing, who wish to understand the issues of DAI.

Table of contents

  1. Front Cover
  2. Distributed Artificial Intelligence
  3. Copyright Page
  4. Table of Contents
  5. Foreword (1/2)
  6. Foreword (2/2)
  7. Part I: Theoretical Issues
    1. Chapter 1. Decision Procedures
      1. Abstract
      2. 1.1 Introduction
      3. 1.2 Solutions to Problems of Interaction
      4. 1.3 Notation
      5. 1.4 Rationality
      6. 1.5 Uniform Rationality
      7. 1.6 Global Rationality
      8. 1.7 Communication
      9. 1.8 An Application
      10. 1.9 Conclusion
      11. Acknowledgements
      12. References
    2. Chapter 2. Cooperation Through Communication in a Distributed Problem Solving Network
      1. Abstract
      2. 2.1 Introduction
      3. 2.2 Cooperation
      4. 2.3 Distributed Problem Solving
      5. 2.4 Coherence and Communication (1/2)
      6. 2.4 Coherence and Communication (2/2)
      7. 2.5 Planning for Problem Solving (1/2)
      8. 2.5 Planning for Problem Solving (2/2)
      9. 2.6 Increasing Network Coherence
      10. 2.7 Conclusions and Future Research
      11. Acknowledgements
      12. References
    3. Chapter 3. Instantiating Descriptions of Organizational Structures
      1. Abstract
      2. 3.1 Introduction
      3. 3.2 An Example (1/2)
      4. 3.2 An Example (2/2)
      5. 3.3 Describing Organizational Structures with EFIGE (1/3)
      6. 3.3 Describing Organizational Structures with EFIGE (2/3)
      7. 3.3 Describing Organizational Structures with EFIGE (3/3)
      8. 3.4 Instantiating a Description
      9. 3.5 Status and Ongoing Research (1/2)
      10. 3.5 Status and Ongoing Research (2/2)
      11. Appendix A: The Complete Constraint Solution Algorithm
      12. Appendix B: Domain Specific Functions
      13. Acknowledgements
      14. References
  8. Part II: Architectures and Languages
    1. Chapter 4. The Architecture of the Agora Environment
      1. Abstract
      2. 4.1 Introduction
      3. 4.2 Agora's Architecture
      4. 4.3 The Agora Virtual Machine
      5. 4.4 Frameworks
      6. 4.5 Example System Built with Agora (1/2)
      7. 4.5 Example System Built with Agora (2/2)
      8. 4.6 Conclusions
      9. Acknowledgements
      10. References
    2. Chapter 5. MACE: A Flexible Testbed for Distributed AI Research
      1. Abstract
      2. 5.1 Introduction
      3. 5.2 What is a MACE Agent?
      4. 5.3 What Agents Know
      5. 5.4 How Agents Sense Their World
      6. 5.5 How Agents Act: Engines
      7. 5.6 Organizations
      8. 5.7 Describing Agents: The ADL and Description Database
      9. 5.8 An Example: the Contract Net in MACE
      10. 5.9 An Environment for Building and Experimenting with Agents
      11. 5.10 Experiences and Conclusions
      12. Acknowledgements
      13. References
    3. Chapter 6. AF: A Framework for Real-Time Distributed Cooperative Problem Solving
      1. Abstract
      2. 6.1 Introduction
      3. 6.2 Activation Framework Objects, Messages, and Frameworks (1/2)
      4. 6.2 Activation Framework Objects, Messages, and Frameworks (2/2)
      5. 6.3 Current Status
      6. 6.4 Commentary
      7. Acknowledgements
      8. References
    4. Chapter 7. A Connectionist Encoding of Semantic Networks
      1. Abstract
      2. 7.1 Introduction
      3. 7.2 A Restricted Language for Representing Conceptual Knowledge
      4. 7.3 Connectionist Encoding (1/3)
      5. 7.3 Connectionist Encoding (2/3)
      6. 7.3 Connectionist Encoding (3/3)
      7. 7.4 Some Examples
      8. 7.5 Conclusions
      9. Acknowledgements
      10. References
    5. Chapter 8. Semi-Applicative Programming: Examples of Context Free Recognizers
      1. Abstract
      2. 8.1 Semi-Applicative Programming
      3. 8.2 Detailed Discussion of our Approach (1/2)
      4. 8.2 Detailed Discussion of our Approach (2/2)
      5. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (1/6)
      6. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (2/6)
      7. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (3/6)
      8. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (4/6)
      9. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (5/6)
      10. 8.3 Research Results: Derivation of Recognition Algorithmsfor CNF Grammars (6/6)
      11. 8.4 Conclusion
      12. Acknowledgements
      13. References
  9. Part III: Applications and Examples
    1. Chapter 9. DAI for Document Retrieval: The MINDS Project
      1. Abstract
      2. 9.1 Introduction
      3. 9.2 Document Knowledge and Metaknowledge
      4. 9.3 System Architecture
      5. 9.4 Updating Metaknowledge
      6. 9.5 Heuristic Refinement Testbed
      7. 9.6 Implementation (1/2)
      8. 9.6 Implementation (2/2)
      9. 9.7 Summary
      10. References
    2. Chapter 10. Manufacturing Experience with the Contract Net
      1. Abstract
      2. 10.1 A Contract Net for Manufacturing Control
      3. 10.2 Analyzing the Factory Problem
      4. 10.3 Tailoring the Contract Net for the Factory Floor (1/3)
      5. 10.3 Tailoring the Contract Net for the Factory Floor (2/3)
      6. 10.3 Tailoring the Contract Net for the Factory Floor (3/3)
      7. 10.4 Summary
      8. Acknowledgements
      9. References
    3. Chapter 11. Participant Systems for Cooperative Work
      1. Abstract
      2. 11.1 Introduction
      3. 11.2 Background (1/2)
      4. 11.2 Background (2/2)
      5. 11.3 Participant Systems (1/3)
      6. 11.3 Participant Systems (2/3)
      7. 11.3 Participant Systems (3/3)
      8. 11.4 Related Work (1/2)
      9. 11.4 Related Work (2/2)
      10. 11.5 Conclusion
      11. Acknowledgements
      12. References
    4. Chapter 12. Distributed Artificial Intelligence: An Annotated Bibliography
      1. Abstract
      2. Advanced Information and Decision Systems
      3. AT&T Bell Laboratories
      4. Boeing Advanced Technology Center for Computer Sciences
      5. Carnegie-Mellon University
      6. Columbia University
      7. Defense Research Establishment
      8. Harvard University
      9. IBM Research Laboratory
      10. IBM Zurich Research Laboratory
      11. Information Sciences Division, Electrotechnical Laboratory
      12. INRIA Sophia-Antipolis
      13. Institute for Co-ordination of Computer Techniques
      14. Institute for New Generation Computer Technology
      15. Laboratoire d' Autamatique
      16. Louisiana State University
      17. Massachusetts Institute of Technology
      18. NASA Langley Research Center
      19. Naval Air Development Center
      20. Naval Oceans Systems Center
      21. Northwestern University
      22. Ohio State University
      23. Rand Corporation
      24. Schlumberger-Doll Research
      25. SRI International
      26. Stanford University (1/2)
      27. Stanford University (2/2)

Product information

  • Title: Distributed Artificial Intelligence
  • Author(s): Michael N. Huhns
  • Release date: December 2012
  • Publisher(s): Morgan Kaufmann
  • ISBN: 9780323137591