Problem solving with multi-agent systems appears to be a very active research area nowadays. We present in this talk an overview of some works around distributed Constraint Satisfaction Problems and we point out some recent results about phase transition and emergence in multi-agents resolution of such problems. We also point out the links and differences with distributed or randomized algorithms.
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In this paper we argue that mind is emerging. First we present a Knowledge Representation Model whose aim is to record in a clever way the “facts and events” of a user. The main features of our model are: (1) Personal knowledge: no bottleneck, responsibility for validity. (2) Persistent storage: forces to record truths that are not supposed to change. (3) Instance-driven: knowledge units may exist even without classification or explicit rules to handle them. (4) Unicity-oriented: knowledge is composed of atomic pieces the existence of which is not supposed to be debatable. We show in what way it can be considered as an emergent organisation of memory, and then briefly discuss its application to training in the ELeGI1 EEC project (European Learning Grid Infrastructure).
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