This paper presents snlp+ebl, the first implementation of explanation based learning techniques for a partial order planner. We describe the basic learning framework of snlp+ebl, ...
paper, we present an abstract framework for learning a finite domain constraint solver modeled by a set of operators enforcing a consistency. The behavior of the consistency to be...
Arnaud Lallouet, Thi-Bich-Hanh Dao, Andrei Legtche...
This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
This article deals with the problem of collaborative learning in a multi-agent system. Here each agent can update incrementally its beliefs B (the concept representation) so that ...
Gauvain Bourgne, Amal El Fallah-Seghrouchni, Henry...
The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requirements s...