Titlebook: Distributed Constraint Satisfaction; Foundations of Coope Makoto Yokoo Book 2001 Springer-Verlag Berlin Heidelberg 2001 Agent Cooperation.A

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Antarctic Soils and Climate Change,of sensor data. These agents produce possible interpretations and try to build a globally consistent interpretation. If an agent makes incorrect interpretations because of errors in the process—for example, noise on the sensor data—there may be a situation where no globally consistent interpretation exists.

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Summary and Future Issues,ybrid-type algorithm of backtracking and iterative improvement, and investigated which kinds of problem instances are most difficult for hill-climbing algorithms. Also, we showed an extension of the basic CSP formalization called partial CSPs.

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Distributed Consistency Algorithm,distributed system that achieves arc-consistency for resource allocation tasks was developed. This system also maintains arc-consistency, i.e., it can re-achieve arc-consistency after dynamic changes in variables/values/constraints with a small amount of computational effort by utilizing dependencies.

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Handling Over-Constrained Situations,of sensor data. These agents produce possible interpretations and try to build a globally consistent interpretation. If an agent makes incorrect interpretations because of errors in the process—for example, noise on the sensor data—there may be a situation where no globally consistent interpretation exists.

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1619-7119 t Systems (MAS) that are concerned with finding a consistent combination of agent actions can he formalized as dis­ tributed CSPs. Therefore, we can consid(~r distributed CSPs as a general framework for MAS, 978-3-642-64020-9978-3-642-59546-2Series ISSN 1619-7119 Series E-ISSN 1866-7333

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Handling Multiple Local Variables, the local problem of each agent becomes large and complex. Although these algorithms can be applied to the situation where one agent has multiple local variables by the following methods, both methods are neither efficient nor scalable to large problems.