Expressivity and control in limited reasoning

Abstract. Real agents (natural or artificial) are limited in their reasoning capabilities. In this paper, we present a general framework for modeling limited reasoning based on approximate reasoning and discuss its properties. We start from Cadoli and Schaerf's approximate entailment. We first extend their system to deal with the full language of propositional logic. A tableau inference system is proposed for the extended system together with a sub-classical semantics; it is shown that this new approximate reasoning system is sound and complete with respect to this semantics. We show how this system can be incrementally used to move from one approximation to the next until the reasoning limitation is reached. We note that although the extension is more expressive than the original system, it offers less control over the approximation process. We then suggest how we can recover control while keeping the increased expressivity

Graph theoretical structures in logic programs and default theories

In this paper we present a graph representation of logic programs and default theories. We show that many of the semantics proposed for logic programs can be expressed in terms of notions emerging from graph theory, establishing in this way a link between the fields. Namely the stable models, the partial stable models, and the well-founded semantics correspond respectively to the kernels, semikernels and the initial acyclic part of the associated graph. This link allows us to consider both theoretical problems (existence, uniqueness) and computational problems (tractability, algorithms, approximations) from a more abstract and rather combinatorial point of view. It also provides a clear and intuitive understanding about how conflicts between rules are resolved within the different semantics. Furthermore, we extend the basic framework developed for logic programs to the case of Default Logic by introducing the notions of partial, deterministic and well-founded extensions for default theories. These semantics capture different ways of reasoning with a default theory

Approximate Inference in Default Logic and Circumscription

We propose a technique for dealing with the high complexity of reasoning under propositional default logic and circumscription. The technique is based on the notion of approximation: A logical consequence relation is computed by means of sound and progressively “more complete” relations, as well as complete and progressively “more sound” ones. Both sequences generated in this way converge to the original consequence relation and are easier to compute. Moreover they are given a clear semantics based on multivalued logic. With this technique unsoundness and incompleteness are introduced in a controlled way and precisely characterized