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Présentation Coordination Of Large - Scale Multiagent Systems Format Broché
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Résumé :
Challenges arise when the size of a group of cooperating agents is scaled to hundreds or thousands of members. In domains such as space exploration, military and disaster response, groups of this size (or larger) are required to achieve extremely complex, distributed goals. To effectively and efficiently achieve their goals, members of a group need to cohesively follow a joint course of action while remaining flexible to unforeseen developments in the environment. Coordination of Large-Scale Multiagent Systems provides extensive coverage of the latest research and novel solutions being developed in the field. It describes specific systems, such as SERSE and WIZER, as well as general approaches based on game theory, optimization and other more theoretical frameworks. It will be of interest to researchers in academia and industry, as well as advanced-level students.
Sommaire:
Part I Effects of Scaling Coordination: The Effects of Locality and Asymmetry in Large-Scale Multiagent MDPs.- A Study of Scalability Properties in Robotic Teams.- Comparing Three Approaches to Large-Scale Coordination.- Part II Scaling Existing Coordination Approaches: Decentralized Partner Finding in Multi-Agent Systems.- Distributed Coordination of an Agent Society Based on Obligations and Commitments to Negotiated Agreements.- A Family of Graphical-Game-Based Algorithms for Distributed Constraint Optimization Problems.- Key-Based Coordination Strategies: Scalability Issues.- Designing Agent Utilities for Coordinated, Scalable and Robust Multi-Agent Systems.- Part III New Approaches for Large Scale Coordination: Learning Scalable Coaltion Formation in an Organizational Content.- Multi-Agent Coordination in Open Environments.- Mobile Agents.- WIZER: Automated Model Improvement in Multi-Agent Social-Network Systems.- Part IV Robustness and Flexibility in Large-Scale Multi-Agent Systems: Towards Flexible Coordination of Large Scale Multi-Agent Teams.- Techniques for Robust Planning in Degradable Multiagent Systems.
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