This paper investigates the appropriateness of formal dialectics as a basis for non-monotonic reasoning and defeasible reasoning that takes computational limits seriously. Rules that can come into con ict should be regarded as policies, which are inputs to deliberative processes. Dialectical protocols are appropriate for such deliberations when resources are bounded and search is serial. AI, it is claimed here, is now perfectly positioned to correct many misconceptions about reasoning that have resulted from mathematical logic's enormous success in this century: among them, (1) that all reasons are demonstrative, (2) that rational belief is constrained, not constructed, (3) that process and disputation are not essential to reasoning. AI mainly provides new impetus to formalize the alternative (but older) conception of reasoning, and AI provides mechanisms with which to create compelling formalism that describes the control of processes. The technical contributions here are: the partial justi cation of dialectic based on controlling search; the observation that non-monotonic reasoning can be subsumed under certain kinds of dialectics; the portrayal of inference in knowledge bases as policy reasoning; the review of logics of dialogue and proposed extensions; and the pre-formal and initial formal discussion of aspects and variations of dialectical systems with non-demonstrative reasons.
REF investigates the appropriateness of formal dialectics as a basis for non-monotonic reasoning and defeasible reasoning.
Process And Policy: Resource-Bounded Non-Demonstrative Reasoning
Computer Science