Distributed Artificial Intelligence: Theory and Praxis
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Distributed Artificial Intelligence: Theory and Praxis

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Description

Distributed AI is the branch of AI concerned with how to coordinate behavior among a collection of semi-autonomous problem-solving agents: how they can coordinate their knowledge, goals and plans to act together, to solve joint problems, or to make individually or globally rational decisions in the face of uncertainty and multiple, conflicting perspectives. Distributed, coordinated systems of problem solvers are rapidly becoming practical partners in critical human problem-solving environments, and DAI is a rapidly developing field of both application and research, experiencing explosive growth around the world.
This book presents a collection of articles surveying several major recent developments in DAI. The book focuses on issues that arise in building practical DAI systems in real-world settings, and covers work undertaken in a number of major research and development projects in the U.S. and in Europe. It provides a synthesis of recent thinking, both theoretical and applied, on major problems of DAI in the 1990s.
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Product details

  • Hardback | 235 pages
  • 164.6 x 242.8 x 20.3mm | 535.25g
  • Dordrecht, Netherlands
  • English
  • 1993 ed.
  • VII, 235 p.
  • 0792315855
  • 9780792315858

Table of contents

Introduction; N.M. Avouris, L. Gasser. An Overview of DAI; L. Gasser. DAI Approaches to Coordination; L. Gasser. Using Reactive Multi-Agent Systems in Simulation and Problem Solving; J. Ferber, A. Drogoul. Object-Based Concurrent Programming and DAI; L. Gasser, J.-P. Briot. A Software Engineering Perspective on Multi-Agent System Design: Experience in the Development of MADE; G.M.P. O'Hare, M.J. Wooldridge. Prototyping Multi-Agent Systems: A Case Study; G. Lekkas, M.H. Van Liedekerke. User Interface Design for DAI Applications: An Overview; N.M. Avouris. Methodological Issues of DAI Applications Interface Design: Transparency Analysis; L.E. Hall, N.M. Avouris. ARCHON: Theory and Practice; N.R. Jennings, T. Wittig. EMMA: An Architecture for Enterprise Modeling and Integration; K. Sycara, M. Roboam. Teaching Distributed Artificial Intelligence; J. Rosenschein. Index.
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