Multiagent Incremental Learning in Networks
Soldano, Henry; Maudet, Nicolas; Seghrouchni, Amal El Fallah; Bourgne, Gauvain (2008), Multiagent Incremental Learning in Networks, Intelligent Agents and Multi-Agent Systems 11th Pacific Rim International Conference on Multi-Agents, PRIMA 2008, Hanoi, Vietnam, December 15-16, 2008. Proceedings, Springer : Berlin, p. 109-120. http://dx.doi.org/10.1007/978-3-540-89674-6_14
TypeCommunication / Conférence
Conference title11th Pacific Rim International Conference on Multi-Agents, PRIMA 2008
Conference countryViêt Nam
Book titleIntelligent Agents and Multi-Agent Systems 11th Pacific Rim International Conference on Multi-Agents, PRIMA 2008, Hanoi, Vietnam, December 15-16, 2008. Proceedings
Series titleLecture Notes in Computer Science
MetadataShow full item record
Abstract (EN)This paper investigates incremental multiagent learning in structured networks. Learning examples are incrementally distributed among the agents, and the objective is to build a common hypothesis that is consistent with all the examples present in the system, despite communication constraints. Recently, different mechanisms have been proposed that allow groups of agents to coordinate their hypotheses. Although these mechanisms have been shown to guarantee (theoretically) convergence to globally consistent states of the system, others notions of effectiveness can be considered to assess their quality. Furthermore, this guaranteed property should not come at the price of a great loss of efficiency (for instance a prohibitive communication cost). We explore these questions theoretically and experimentally (using different boolean formulas learning problems).
Subjects / KeywordsStructured networks
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