Formalizing Practical Reasoning Under Uncertainty: An Argumentation-Based Approach

Practical reasoning (PR), as advocated by philosophers is concerned by reasoning about what agents should do. It follows mainly two steps. A deliberation one for identifying the goals to be achieved, and a means-ends reasoning step for choosing the ways of achieving them. The PR literature has mainly proposed informal patterns of inference for describing such a process in simple situations. Moreover, this line of thoughts has influenced some AI researchers who proposed BDI architectures. Namely, agents are supposed to have beliefs and to entertain desires from which they elicit the intentions to be pursued. The interest of such an approach is to emphasize some aspects involved in a decision problem that are not explicitly dealt with by classical approaches, in particular the feasibility of actions, and the generation of agent's goals. However, there is no complete formalization of the whole PR in the BDI literature. The paper aims at providing an abstract framework for PR. It is based on argumentation techniques for both deliberation and for selecting subsets of compatible actions, possibly in presence of uncertainty. The framework returns a consistent subset of desires as well as ways/actions for achieving them. Such actions are called intentions. We show that these intentions are generated via some decision criteria. Thus, depending on whether the agent has an optimistic or a pessimistic attitude, the set of intentions may not be the same. Indeed, we show that PR leads to a generalized decision making problem, where instead of comparing atomic actions, one compares sets of actions.