This book provides a tutorial introduction to modern techniques for representing and reasoning about qualitative preferences with respect to a set of alternatives. The syntax and semantics of several languages for representing preference languages, including CP-nets, TCP-nets, CI-nets, and CP-theories, are reviewed. Some key problems in reasoning about preferences are introduced, including determining whether one alternative is preferred to another, or whether they are equivalent, with respect to a given set of preferences. These tasks can be reduced to model checking in temporal logic. Specifically, an induced preference graph that represents a given set of preferences can be efficiently encoded using a Kripke Structure for Computational Tree Logic (CTL). One can translate preference queries with respect to a set of preferences into an equivalent set of formulae in CTL, such that the CTL formula is satisfied whenever the preference query holds. This allows us to use a model checker to reason about preferences, i.e., answer preference queries, and to obtain a justification as to why a preference query is satisfied (or not) with respect to a set of preferences. This book defines the notions of the equivalence of two sets of preferences, including what it means for one set of preferences to subsume another, and shows how to answer preferential equivalence and subsumption queries using model checking. Furthermore, this book demontrates how to generate alternatives ordered by preference, along with providing ways to deal with inconsistent preference specifications. A description of CRISNER—an open source software implementation of the model checking approach to qualitative preference reasoning in CP-nets, TCP-nets, and CP-theories is included, as well as examples illustrating its use.
This is the first book to offer a cohesive treatment of the research problems in collaborative knowledge acquisition from semantically disparate information sources & approaches for addressing the problems. The book discusses the fundamental advances in this area covering a broad range & complexity of research issues. The approach taken incorporates a synergistic synthesis of insights, algorithms & results drawn from multiple areas including: • Artificial Intelligence – especially machine learning, data mining, knowledge representation & inference, intelligent agents & multi-agent systems; • Information Systems – especially databases, information integration, semantic web; & • Distributed computing & software engineering (e.g. service-oriented computing). Written for researchers & graduate students as well as advanced practitioners in data mining, semantic technologies, AI, Information integration, the semantic web, & information systems, this accessible self-contained survey will be a valuable reference tool.
This book constitutes the refereed proceedings of the Fourth International Colloquium on Grammatical Inference, ICGI-98, held in Ames, Iowa, in July 1998. The 23 revised full papers were carefully reviewed and selected for inclusion in the book from a total of 35 submissions. The book addresses a wide range of grammatical inference theory such as automata induction, grammar induction, automatic language acquisition, etc. as well as a variety of applications in areas like syntactic pattern recognition, adaptive intelligent agents, diagnosis, computational biology, data mining, and knowledge discovery.
This book provides a tutorial introduction to modern techniques for representing and reasoning about qualitative preferences with respect to a set of alternatives. The syntax and semantics of several languages for representing preference languages, including CP-nets, TCP-nets, CI-nets, and CP-theories, are reviewed. Some key problems in reasoning about preferences are introduced, including determining whether one alternative is preferred to another, or whether they are equivalent, with respect to a given set of preferences. These tasks can be reduced to model checking in temporal logic. Specifically, an induced preference graph that represents a given set of preferences can be efficiently encoded using a Kripke Structure for Computational Tree Logic (CTL). One can translate preference queries with respect to a set of preferences into an equivalent set of formulae in CTL, such that the CTL formula is satisfied whenever the preference query holds. This allows us to use a model checker to reason about preferences, i.e., answer preference queries, and to obtain a justification as to why a preference query is satisfied (or not) with respect to a set of preferences. This book defines the notions of the equivalence of two sets of preferences, including what it means for one set of preferences to subsume another, and shows how to answer preferential equivalence and subsumption queries using model checking. Furthermore, this book demontrates how to generate alternatives ordered by preference, along with providing ways to deal with inconsistent preference specifications. A description of CRISNER—an open source software implementation of the model checking approach to qualitative preference reasoning in CP-nets, TCP-nets, and CP-theories is included, as well as examples illustrating its use.
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