Knowledge Acquisition Modeling Through Dialogue Between Cognitive Agents

This article tackles learning and communication between cognitive artificial agents. Our focus is on dialogue as the only way for agents to acquire knowledge, as it often happens in natural situations. Since this restriction has scarcely been studied in artificial intelligence (AI) until now; this research aims to provid a dialogue model devoted to knowledge acquisition. It allows two agents, in a “teacher” – “student” relationship, to exchange information with a learning incentive (on behalf of the student). The article first defines the nature of the addressed agents, the types of relation they maintain, and the structure and contents of their knowledge base. It continues by describing the different goals of learning, their realization, and the solutions provided for problems encountered by agents. A general architecture is then established and comment on the part of the theory implementation is given. The conclusion talks about the achievements carried out and the potential improvement of this work.