Abstract
We propose an efficient method to evaluate a large class of history-based policies written as logic programs. To achieve this, we dynamically compute, from a given policy set, a finite subset of the history required and sufficient to evaluate the policies. We maintain this history by monitoring rules and transform the policies into a non history-based form. We further formally prove that evaluating history-based policies can be reduced to an equivalent, but more efficient, evaluation of the non history-based policies together with the monitoring rules.
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Lobo, J., Ma, J., Russo, A., Lupu, E., Calo, S., Sloman, M. (2011). Refinement of History-Based Policies. In: Balduccini, M., Son, T.C. (eds) Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning. Lecture Notes in Computer Science(), vol 6565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20832-4_18
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DOI: https://doi.org/10.1007/978-3-642-20832-4_18
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