Efficiently implementing GOLOG with answer set programming

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Abstract

In this paper we investigate three different approaches to encoding domain-dependent control knowledge for Answer-Set Planning. Starting with a standard implementation of the action description language B, we add control knowledge expressed in the GOLOG logic programming language. A naive encoding, following the original definitions of Levesque et al., is shown to scale poorly. We examine two alternative codings based on the transition semantics of ConGOLOG. We show that a speed increase of multiple orders of magnitude can be obtain by compiling the GOLOG program into a finitestate machine representation.

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APA

Ryan, M. (2014). Efficiently implementing GOLOG with answer set programming. In Proceedings of the National Conference on Artificial Intelligence (Vol. 3, pp. 2352–2357). AI Access Foundation. https://doi.org/10.1609/aaai.v28i1.9026

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