An Adaptative Multi-Agent System to Co-Construct an Ontology from Texts with an Ontologist

Abstract

Ontologies are one of the most used representations to model the domain knowledge. An ontology consists of a set of concepts connected by semantic relations. The construction and evolution of an ontology are complex and time-consuming tasks. This paper presents DYNAMO-MAS, an Adaptive Multi-Agent System (AMAS) that automates these tasks by co-constructing an ontology from texts with an ontologist. Terms and concepts of a given domain are agentified and they act, according to the AMAS approach, by solving the non cooperative situations they locally perceive at runtime. These agents cooperate to determine their position in the AMAS (that is the ontology) thanks to (i) lexical relations between terms, (ii) some adaptive mechanisms enabling addition, removing or moving of new terms, of concepts and of relations in the ontology as well as (iii) feedbacks from the ontologist about the propositions given by the AMAS. This paper focuses on the instantiation of the AMAS approach to this difficult problem. It presents the architecture of DYNAMO-MAS, and details the cooperative behaviors of the two types of agents we defined for ontology evolution. Finally evaluations made on three different ontologies are given in order to show the genericity of our solution.