Truth and Modality for Knowledge Representation

An artificial agent that represents what it believes, knows and holds to be true must reason about those states without falling into the paradoxes that have troubled logicians for centuries. Raymond Turner's compact study, published in 1990, brings the logic community's recent work on truth and modality to bear on knowledge representation in AI. He gives an accessible account of the semantic theories of truth developed by Kripke, Gupta, Herzberger, Gilmore, Aczel and Feferman, each an attempt to cope with the constraints the semantic and logical paradoxes impose.

From these theories Turner extracts logics that he then uses to build accounts of modality, propositions and properties, working through fixpoints, stable truth, Frege structures and predicative modality. It is a clear bridge between philosophical logic and artificial intelligence, for researchers and graduate students who want the formal foundations laid out properly.