Ulteriori informazioni
An Application Science For Multi-Agent Systems addresses the complexity of choosing which multi-agent control technologies are appropriate for a given problem domain or a given application. Without such knowledge, when faced with a new application domain, agent developers must rely on past experience and intuition to determine whether a multi-agent system is the right approach, and if so, how to structure the agents, how to decompose the problem, and how to coordinate the activities of the agents, and so forth. This unique collection of contributions, written by leading international researchers in the agent community, provides valuable insight into the issues of deciding which technique to apply and when it is appropriate to use them. The contributions also discuss potential trade-offs or caveats involved with each decision.
An Application Science For Multi-Agent Systems is an excellent reference for anyone involved in developing multi-agent systems.
Sommario
An Application Science for Multi-Agent Systems; T. Wagner.
Coordination Challenges for Autonomous Spacecraft; B.J. Clement, A.C. Barrett.
A Framework for Evaluation of Multi-Agent System Approaches to Logistics Network Management; P. Davidsson, F. Wernstedt.
Centralized Versus Decentralized Coordination: Two Application Case Studies; T. Wagner, J. Phelps, V. Guralnik.
A Complex Systems Perspective on Collaborative Design; M. Klein, H. Sayama, P. Faratin, Y. Bar-Yam.
Multi-Agent System Interaction Protocols in a Dynamically Changing Environment; M. Purvis, S. Cranefield, M. Nowostawski, M. Purvis.
Challenges to Scaling-Up Agent Coordination Strategies; E.H. Durfee.
Roles in MAS: Managing the Complexity of Tasks and Environments; I. Partsakoulakis, G. Vouros.
An Evolutionary Framework for Large-Scale Experimentation in Multi-Agent Systems; A. Babanov, W. Ketter, M. Gini.
Application Characteristics Motivating Adaptive Organizational Capabilities within Multi-Agent Systems; K.S. Barber, M.T. MacMahon.
Applying Coordination Mechanisms for Dependency Relationships under Various Environments; Wei Chen, K. Decker.
Performance Models for Large Scale Multi-Agent Systems: A Distributed POMDP-Based Approach; Hyuckchul Jung, M. Tambe.
Index.
Riassunto
An Application Science For Multi-Agent Systems addresses the complexity of choosing which multi-agent control technologies are appropriate for a given problem domain or a given application. Without such knowledge, when faced with a new application domain, agent developers must rely on past experience and intuition to determine whether a multi-agent system is the right approach, and if so, how to structure the agents, how to decompose the problem, and how to coordinate the activities of the agents, and so forth. This unique collection of contributions, written by leading international researchers in the agent community, provides valuable insight into the issues of deciding which technique to apply and when it is appropriate to use them. The contributions also discuss potential trade-offs or caveats involved with each decision.
An Application Science For Multi-Agent Systems is an excellent reference for anyone involved in developing multi-agent systems.
