Abstract
A logic allows one to express statements (axioms) that are, perhaps approximately, true of the world. A model is a particular object that is similar to, or “models”, the world. For example, the growing field of model checking involves formal models of the behavior of physical computer chips. Bayesian networks, MPDs, and POMDPs are models of (real) probabilistic environments. This paper argues that world-modeling is more natural that world-axiomatizing. The main technical result is an algorithm for exactly computing the asymptotic average reward of a robot controller written in a high level programming language when run in a world model also defined in a high level language.
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McAllester, D. (1999). World-Modeling vs. World-Axiomatizing. In: Gelfond, M., Leone, N., Pfeifer, G. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 1999. Lecture Notes in Computer Science(), vol 1730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46767-X_29
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DOI: https://doi.org/10.1007/3-540-46767-X_29
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