An Argumentation-based Approach for Identifying and Dealing with Incompatibilities among Procedural Goals
This work addresses goal incompatibility in practical reasoning for AI agents, but it is incremental as it builds on existing forms of incompatibility and applies known argumentation frameworks.
The paper tackles the problem of identifying and resolving incompatibilities among an intelligent agent's procedural goals during deliberation, proposing an argumentation-based approach that defines incompatibilities through conflicts in plans and uses argumentation semantics for goal selection, demonstrated in a modified 'cleaner world' scenario.
During the first step of practical reasoning, i.e. deliberation, an intelligent agent generates a set of pursuable goals and then selects which of them he commits to achieve. An intelligent agent may in general generate multiple pursuable goals, which may be incompatible among them. In this paper, we focus on the definition, identification and resolution of these incompatibilities. The suggested approach considers the three forms of incompatibility introduced by Castelfranchi and Paglieri, namely the terminal incompatibility, the instrumental or resources incompatibility and the superfluity. We characterise computationally these forms of incompatibility by means of arguments that represent the plans that allow an agent to achieve his goals. Thus, the incompatibility among goals is defined based on the conflicts among their plans, which are represented by means of attacks in an argumentation framework. We also work on the problem of goals selection; we propose to use abstract argumentation theory to deal with this problem, i.e. by applying argumentation semantics. We use a modified version of the "cleaner world" scenario in order to illustrate the performance of our proposal.