Intelligent Problem-independent Tool for Plausible Inference

Abstract

The extending of the existing arsenal of formal man-machine procedures for decision making with new inference mechanisms, modelling the human style of reasoning, will lead to expanding the participation of the computer in the man-machine system. For this purpose it is necessary to develop new methods and tools for increasing the communicability between man and the computer, not only at a linguistic, but also at a semantic level, namely, the machine inference should be brough close to the human reasoning, which is characterized by the ability to manipulate with incomplete, uncertain and unreliable knowledge and can reason nonmonotonously. The paper deals with an approach, towards creating a nonmonotonic inference mechanism, which allows work with incomplete and uncertain information. This approach is developed on the basis of the human plausible reasoning schemes. Knowledge and control organization and some main functions, describing the most important plausible reasoning schemes are presented. The suggested problem-independent plausible inference mechanism can be implemented in various man-machine systems and especially in expert systems.