Automata implementation

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Norman Foo (ed

The 12th Australian Joint Conference on Artificial Intelligence (AI'QQ) held in Sydney, Australia, 6-10 December 1999, is the latest in a series of annual re­ gional meetings at which advances in artificial intelligence are reported. This series now attracts many international papers, and indeed the constitution of the program committee reflects this geographical diversity. Besides the usual tutorials and workshops, this year the conference included a companion sympo­ sium at which papers on industrial appUcations were presented. The symposium papers have been published in a separate volume edited by Eric Tsui. Ar99 is organized by the University of New South Wales, and sponsored by the Aus­ tralian Computer Society, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Computer Sciences Corporation, the KRRU group at Griffith University, the Australian Artificial Intelligence Institute, and Neuron- Works Ltd. Ar99 received over 120 conference paper submissions, of which about o- third were from outside Australia. Prom these, 39 were accepted for regular presentation, and a further 15 for poster display. These proceedings contain the full regular papers and extended summaries of the poster papers. All papers were refereed, mostly by two or three reviewers selected by members of the program committee, and a list of these reviewers appears later. The technical program comprised two days of workshops and tutorials, fol­ lowed by three days of conference and symposium plenary and paper sessions.

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Areski Nait Abdallah

This book presents the foundations of reasoning with partial information and a theory of common sense reasoning based on monotonic logic and partial structures. This theory was designed specifically for the needs of practicing computer scientists and provides easily implementable algorithms. Starting from first principles, following the logic of discovery of Karl Popper and Imre Lakatos, and the semantics of programming languages, the book develops a system of reasoning with partial information, and applies it to a comprehensive study of the problem examples from the literature of common sense reasoning. Proof-theoretic and model-theoretic views are considered in the applications, as well as logical problems of theoretical physics, such as issues related to Heisenberg's uncertainty principle. The book points out that customary expositions of common-sense reasoning are based on a flawed non-monotonic reasoning paradigm and that the resulting solutions proposed for major problems, such as the frame problem, are either ad hoc or inadequate. It is shown that non-monotonicity results from hiding information that should not be hidden. The essential research in common-sense reasoning has been developed in isolation from the disciplines of theoretical computer science and classical logic. This work breaks the isolation and establishes deep links. The book will be of interest to computer scientists, mathematicians, logicians, and philosophers interested in the foundations and applications of reasoning with partial information.

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Pierpaolo Degano (ed

This book constitutes the refereed proceedings of the 12th European Symposium on Programming, ESOP 2003, held in Warsaw, Poland, in April 2003. The 25 revised full papers presented together with two invited papers were carefully reviewed and selected from 99 submissions. Among the topics addressed are programming paradigms and their integration, program semantics, calculi of computation, security, advanced type systems, program analysis, program transformation, and practical algorithms based on theoretical developments.

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Ming Li, Akira Maruoka (eds

This book constitutes the refereed proceedings of the 8th International Workshop on Algorithmic Learning Theory, ALT'97, held in Sendai, Japan, in October 1997. The volume presents 26 revised full papers selected from 42 submissions. Also included are three invited papers by leading researchers. Among the topics addressed are PAC learning, learning algorithms, inductive learning, inductive inference, learning from examples, game-theoretical aspects, decision procedures, language learning, neural algorithms, and various other aspects of computational learning theory.