Automata For Branching And Layered Temporal Structures

Automata for Branching and Layered Temporal Structures

Since 2002, FoLLI awards an annual prize for an outstanding dissertation in the fields of Logic, Language, and Information. This book is based on the Ph.D. thesis of Gabriele Puppis, who was the winner of the E.W. Beth dissertation award for 2007. Puppis' thesis focuses on Logic and Computation and, more specifically, on automata-based decidability techniques for time granularity and on a new method for deciding Monadic Second Order theories of trees. The results presented represent a significant step towards a better understanding of the changes in granularity levels that humans make so easily in cognition of time, space, and other phenomena, whereas their logical and computational structure poses difficult conceptual and computational challenges.

Automata for Branching and Layered Temporal Structures

Handbook of Knowledge Representation

Handbook of Knowledge Representation describes the essential foundations of Knowledge Representation, which lies at the core of Artificial Intelligence (AI). The book provides an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. It includes a tutorial background and cutting-edge developments, as well as applications of Knowledge Representation in a variety of AI systems. This handbook is organized into three parts. Part I deals with general methods in Knowledge Representation and reasoning and covers such topics as classical logic in Knowledge Representation; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based problem solving; and Bayesian networks. Part II focuses on classes of knowledge and specialized representations, with chapters on temporal representation and reasoning; spatial and physical reasoning; reasoning about knowledge and belief; temporal action logics; and nonmonotonic causal logic. Part III discusses Knowledge Representation in applications such as question answering; the semantic web; automated planning; cognitive robotics; multi-agent systems; and knowledge engineering. This book is an essential resource for graduate students, researchers, and practitioners in knowledge representation and AI. * Make your computer smarter* Handle qualitative and uncertain information* Improve computational tractability to solve your problems easily