An Overview of the Interrelation Among Agent Systems, Learning Models and Formal Languages

Considering the important role of interdiciplinarity in current research, this article provides an overview of the interchange of methods among three different areas: agent technologies, learning models and formal languages. The ability to learn is one of the most fundamental attributes of the intelligent behaviour. Therefore, any progress in the theory and computer modelling of learning processes is of great significance to fields concerning with understanding intelligence, and this includes, of course, artificial intelligence and intelligent agent technology. Agent technologies can offer good solutions and alternative frameworks to classic models in the area of computing languages and this can benefit formal models of learning. Formal language theory -considered as the stem of theoretical computer science- provides mathematical tools for the description of linguistic phenomena. This theory is central to grammatical inference, a subfield of machine learning. The interest of the interrelation among these disciplines is based on the idea that the collaboration among researchers in these areas can clearly improve their respective fields. Our goal here is to present the state-of-the art of the relationship among these three areas and to emphasize the importance of this interdisciplinary research.