Foundations of Distributed Artificial Intelligence
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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An Overview of Distributed Artificial Intelligence
Logical Foundations of Distributed Artificial Intelligence
Distributed Artificial Intelligence Testbeds
Applications of Distributed Artificial Intelligence
Coordination Techniques for Distributed Artificial
Planning in Distributed Artificial Intelligence
The Evolution of the CooperA Platform
AGenDAA General Testbed for Distributed Artificial
A Framework for Environment Centered
An Environment for the Fabrication
Organizational Intelligence and Distributed Artificial
Distributed Artificial Intelligence References
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ability achieve actions activities agent architecture algorithm Anif application approach ARCHON Artif autonomous agents behavior beliefs blackboard systems Chapter cognitive Cohen commitment communication complex Conf cooperation coordination defined Demazeau described developed Distributed Artificial Intelligence distributed problem solving domain Durfee DVMT dynamic environment evaluation example execution expert systems formal framework function goals heuristics Huhns implementation Intell interaction interface Jennings joint intention knowledge knowledge representation language Lesser logic MAGSY mechanisms modal logic module Morgan Kaufmann multiagent planning multiagent systems n-puzzle negotiation object operators organization organizational partial global planning perfect information perform possible pragmatic Proc programming protocol reactive agents reasoning represent representation request result robots Rosenschein scheduling Section semantics simulation situation situation semantics social specific speech acts strategy structure Syst task telemetry temporal temporal logics testbed theory types uncertainty Werner
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