Learning better together

Gauvain Bourgne Henry Soldano Amal El Fallah Seghrouchni 1
1 SMA - Systèmes Multi-Agents
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : This article addresses collaborative concept learning in a MAS. In a concept learning problem an agent incrementally revises a hypothetical representation of some target concept to keep it consistent with the whole set of examples that it receives from the environment or from other agents. In the program SMILE, this notion of consistency was extended to a group of agents. A surprising experimental result of that work was that a group of agents learns better the difficult boolean problems, than a unique agent receiving the same examples. The first purpose of the present paper is to propose some explanation about such unexpected superiority of collaborative learning. Furthermore, when considering large societies of agents, using pure sequential protocols is unrrealistic. The second and main purpose of this paper is thus to propose and experiment broadcast protocols for collaborative learning.
Type de document :
Communication dans un congrès
European Conference on Artificial Intelligence ECAI 2010, Aug 2010, Lisbon, Portugal. IOS Press, European Conference on Artificial Intelligence ECAI 2010, 215, pp.85-90, Frontiers in Artificial Intelligence and Applications. 〈10.3233/978-1-60750-606-5-85〉
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https://hal.archives-ouvertes.fr/hal-01292553
Contributeur : Lip6 Publications <>
Soumis le : mercredi 23 mars 2016 - 13:27:51
Dernière modification le : jeudi 24 mars 2016 - 01:03:27

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Gauvain Bourgne, Henry Soldano, Amal El Fallah Seghrouchni. Learning better together. European Conference on Artificial Intelligence ECAI 2010, Aug 2010, Lisbon, Portugal. IOS Press, European Conference on Artificial Intelligence ECAI 2010, 215, pp.85-90, Frontiers in Artificial Intelligence and Applications. 〈10.3233/978-1-60750-606-5-85〉. 〈hal-01292553〉

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