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Distributed Artificial Intelligence (DAI) is a dynamic area of research and this book is the first comprehensive, truly integrated exposition of the discipline presenting influential contributions from leaders in the field. Commences with a solid introduction to the theoretical and practical issues of DAI, followed by a discussion of the core research topics--communication, coordination, planning--and how they are related to each other. The third section describes a number of DAI testbeds, illustrating particular strategies commissioned to provide software environments for building and experimenting with DAI systems. The final segment contains contributions which consider DAI from different perspectives.

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Distributed artificial intelligence (DAI) has grown rapidly in recent years and continues to stimulate widespread research activity. Until now, however, no book has provided a comprehensive, unified treatment of DAI--forcing engineers, researchers, and students to comb the professional literature in search of pertinent information.

Foundations of Distributed Artificial Intelligence fills that gap.

This up-to-date collection of contributions from around the globe examines theoretical principles and practical applications, combines a broad view of the field with detailed examinations of specific research topics, and offers superb coverage at both introductory and advanced levels.

The presentation is divided into four parts. Section one covers the fundamentals and necessary background material upon which the second section builds its discussion of communication, coordination, planning, and agency. The third part of the book focuses on the specifics of systems, testbeds, and software environments used in many industrial and practical applications--including ARCHON, IMAGINE, CooperA, AGenDA, TæMS, and Agent Factory. Finally, the book devotes an entire segment to related areas of scientific inquiry, from philosophy and the social sciences to interface design issues for DAI systems. Throughout, the contributors offer real-world examples from their own research to describe various methods, solutions, and approaches in current practice; and relate the information to the larger body of work available on the subject.

For scientists, engineers, and graduate students involved in the study of this discipline, Foundations of Distributed Artificial Intelligence serves as an excellent introductory text, an extremely useful guide to current knowledge, and a bountiful source of ideas for further research.

This is the first book to provide a comprehensive treatment of distributed artificial intelligence, a field that has seen an explosion of research in recent years. The tremendous and growing interest in this field has underscored the need for an up-to-date, integrated reference accessible to both researchers and graduate students.

A comprehensive, unified treatment of this increasingly important area of research including contributions from an international group of leading experts, Foundations of Distributed Artificial Intelligence:
* Treats the various topics at both introductory and advanced levels
* Covers theory and applications, explaining in detail the principles underlying DAI
* Describes and correlates the main research areas of communication, coordination, planning, and agency
* Details specific strategies for the development of software used in building and experimenting with DAI systems
* Correlates DAI to the larger arena of scientific inquiry; particularly philosophy, organizational intelligence, cognitive science, and human-computer interaction
* Reviews major achievements in the field over the past twenty years
* Provides an extensive list of references and numerous resources

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Partial table of contents:
 
 FORMULATIVE READINGS.
 
 Logical Foundations of Distributed Artificial Intelligence (E. Werner).
 
 Distributed Artificial Intelligence Testbeds (K. Decker).
 
 COOPERATION, COORDINATION, AND AGENCY.
 
 Coordination Techniques for Distributed Artificial Intelligence (N. Jennings).
 
 Negotiation Principles (H. Müller).
 
 Planning in Distributed Artificial Intelligence (E. Durfee).
 
 DAI FRAMEWORKS AND THEIR APPLICATIONS.
 
 IMAGINE: An Integrated Environment for Constructing Distributed Artificial Intelligence Systems (D. Steiner).
 
 AGenDA--A General Testbed for Distributed Artificial Intelligence Applications (K. Fischer, et al.).
 
 Agent Factory: An Environment for the Fabrication of Multiagent Systems (G. O'Hare).
 
 RELATED DISCIPLINES.
 
 Philosophy and Distributed Artificial Intelligence: The Case of Joint Intention (R. Tuomela).
 
 User Design Issues for Distributed Artificial Intelligence (L. Hall).
 
 Appendix.
 
 Index.

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