Truth and Modality for Knowledge Representation

Over the past decade there has been a spurt of activity in the logic community around the development of logics of truth and modality. At the same time the literature in artificial intelligence has focused on the development of formalisms that can facilitate more expressive systems of knowledge representation. Raymond Turner brings the two together, putting current research in theories of truth and modalty in a context where it can be directly applied to knowledge representation in AI. The goal is to help AI researchers understand how the intelligent agents that they are developing represent and reason about what they believe, know, and hold to be true. Turner introduces various logics of truth and modality as part of a foundation for the construction of theories of knowledge representation. The development of logics of truth and syntactic modality is a recent phenomenon. Various logicians have developed semantic theories of truth that seek to come to terms with the constraints imposed by the semantic and logical paradoxes. Turner reviews the most recent and influential of these semantic theories and employs them as the basis for the development of logics of truth and modality. In particular, he provides an accessible exposition of the theories of Kripke, Gupta, Herzberger, Gilmore, Aczel, and Feferman. The logics extracted from these semantic theories are subsequently used to develop logics and theories of modality, propositions, and properties.

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