LOGIC PROGRAMMING AND KNOWLEDGE REPRESENTATION

In this paper, we review recent work aimed at the application of declarative logic programming to knowledge representation in artificial intelligence. We consider extensions of the language of definite logic programs by classical (strong) negation, disjunction, and some modal operators and show how each of the added features extends the representational power of the language. We also discuss extensions of logic programming allowing abductive reasoning, meta-reasoning and reasoning in open domains. We investigate the methodology of using these languages for representing various forms of nonmonotonic reasoning and for describing knowledge in specific domains. We also address recent work on properties of programs needed for sucessful applications of this methodology such as consistency, categoricity and complexity.