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    Optimization, games, and quantified constraint satisfaction

    Chen, Hubie and Pal, M. and Kratochvil, J. (2004) Optimization, games, and quantified constraint satisfaction. In: Fiala, J. and Koubek, V. (eds.) 29th International Symposium: Mathematical Foundations of Computer Science. Lecture Notes in Computer Science 3153. Springer, pp. 239-250. ISBN 9783540228233.

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    Abstract

    Optimization problems considered in the literature generally assume a passive environment that does not react to the actions of an agent. In this paper, we introduce and study a class of optimization problems in which the environment plays an active, adversarial role and responds dynamically to the actions of an agent; this class of problems is based on the framework of quantified constraint satisfaction. We formalize a new notion of approximation algorithm for these optimization problems, and consider certain restricted versions of the general problem obtained by restricting the types of constraints that may appear. Our main result is a dichotomy theorem classifying exactly those restricted versions having a constant factor approximation algorithm.

    Metadata

    Item Type: Book Section
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 09 Mar 2021 16:41
    Last Modified: 09 Mar 2021 16:41
    URI: https://eprints.bbk.ac.uk/id/eprint/43353

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