Applying CBR to manage argumentation in MAS

Abstract

The application of argumentation theories and techniques in multi-agent systems has become a prolific area of research. Argumentation allows agents to harmonize two types of disagreement situations: internal, when the acquisition of new information (e.g. about the environment or about other agents) produces incoherences in the agents' mental state; and external, when agents that have different positions about a topic engage in a discussion. The focus of this paper is on the latter type of disagreement situations. In those settings, agents must be able to generate, select and send arguments to other agents that will evaluate them in their turn. An efficient way for agents to manage these argumentation abilities is by using case-based reasoning, which has been successfully applied to argumentation from its earliest beginnings. This reasoning methodology also allows agents to learn from their experiences and therefore, to improve their argumentation skills. This paper analyses the advantages of applying case-based reasoning to manage arguments in multi-agent systems dialogues, identifies open issues and proposes new ideas to tackle them.