Is Plausible Reasoning a Sensible Alternative for Inductive-Statistical Reasoning?

Abstract

The general purpose of this paper is to show a practical instance of how philosophy can benefit from some ideas, methods and techniques developed in the field of Artificial Intelligence (AI). It has to do with some recent claims [4] that some of the most traditional philosophical problems have been raised and, in some sense, solved by AI researchers. The philosophical problem we will deal with here is the representation of non-deductive intra-theoretic scientific inferences. We start by showing the flaws with the most traditional solution for this problem found in philosophy: Hempel’s Inductive-Statistical (I-S) model [5]. After we present a new formal model based on previous works motivated by reasoning needs in Artificial Intelligence [11] and show that since it does not suffer from the problems identified in the I-S model, it has great chances to be successful in the task of satisfactorily representing the non-deductive intra- theoretic scientific inferences.KeywordsScientific ExplanationPlausible ReasoningQuick RecoveryAxiom SchemaParaconsistent Logical SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.