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.
CITATION STYLE
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
Mendeley helps you to discover research relevant for your work.