Abstract
Recently, a new language \(\mathcal{ACC}\) was proposed to integrate answer set programming (ASP) and constraint logic programming (CLP). In this paper, we show that \(\mathcal{ACC}\) can be employed to build a temporally expressive planner for PDDL2.1. Compared with the existing planners, the new approach put less restrictions on the planning problems and is easy to extend with new features like PDDL axioms, thanks to the expressive power of \(\mathcal{ACC}\). More interestingly, it can also leverage the inference engine for \(\mathcal{ACC}\) which has the potential to exploit the best reasoning mechanisms developed in the ASP, SAT and CP communities.
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Bao, F.S., Chintabathina, S., Morales, A.R., Rushton, N., Watson, R., Zhang, Y. (2011). A Temporally Expressive Planner Based on Answer Set Programming with Constraints: Preliminary Design. 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_25
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DOI: https://doi.org/10.1007/978-3-642-20832-4_25
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