Interac-DEC-MDP : Towards the use of interactions in DEC-MDP
Identifieur interne : 006D30 ( Main/Merge ); précédent : 006D29; suivant : 006D31Interac-DEC-MDP : Towards the use of interactions in DEC-MDP
Auteurs : Vincent Thomas ; Christine Bourjot ; Vincent ChevrierSource :
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Abstract
This article presents a new formalism Interac-DEC-MDP whose aim is to introduce the concept of interaction in Decentralized Markov Decision Process and which has been inspired by biology. The aim of this formalism, Interac-DEC-MDP, is to describe and represent interactions among agents. The outcome of interactions is decided collectively by two agents and is in charge of the distribution of local rewards. We have modeled a biological experiment within this formalism. A simple learning algorithm applied on this formalism generates a more efficient collective behavior than without interactions.
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