Multi-Agent Rationality (Lecture Notes in Computer Science) de Magnus Boman

Multi-Agent Rationality: 8th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, MAAMAW'97, Ronneby, Sweden, May 13-16, 1997, Proceedings: Lecture Notes in Computer Science, cartea 1237

Magnus Boman

Walter Van de Velde

This book constitutes the refereed proceedings of the 8th European Workshop on Modelling Autonomous Agents in a Multi-Agent World, MAAMAW'97, held in Ronneby, Sweden, in May 1997.
MAAMAW'97 is devoted to multi-agent rationality, thus reflecting the fact that there is presently a transition in the multi-agent community from the study of individual rationality to the study of group rationality. The volume presents 15 revised full papers selected from a total of 51 submissions; also included are the abstracts of three invited talks. The volume covers all current issues in multi-agent rationality.

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Specificații

ISBN-13: 9783540630777
ISBN-10: 3540630775
Pagini: 276
Ilustrații: XIV, 262 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.39 kg
Ediția:1997
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

Market-aware agents for a multiagent world.- Learning and adoption versus optimization.- Limits of strategic rationality for agents and M-A systems.- Multiagent coordination in antiair defense: A case study.- A service-oriented negotiation model between autonomous agents.- Norms as constraints on real-time autonomous agent action.- Distributed belief revision vs. belief revision in a multi-agent environment: First results of a simulation experiment.- Multi-agent coordination by communication of evaluations.- Causal reasoning in multi-agent systems.- The reorganization of societies of autonomous agents.- Adaptive selection of reactive/deliberate planning for the dynamic environment.- Distributed problem-solving as concurrent theorem proving.- Commitments among autonomous agents in information-rich environments.- Making a case for Multi-Agent Systems.- Learning network designs for asynchronous teams.- Building multi-agent systems with CORRELATE.- Modelling an agent's mind and matter.- Delegation conflicts.