Temporal planning with continuous change
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
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Integrating answer set programming and constraint logic programming
Annals of Mathematics and Artificial Intelligence
Planning with problems requiring temporal coordination
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PDDL2.1: an extension to PDDL for expressing temporal planning domains
Journal of Artificial Intelligence Research
Temporal planning using subgoal partitioning and resolution in SGPlan
Journal of Artificial Intelligence Research
When is temporal planning really temporal?
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
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Multivalued action languages with constraints in CLP(FD)
ICLP'07 Proceedings of the 23rd international conference on Logic programming
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Recently, a new language ACC was proposed to integrate answer set programming (ASP) and constraint logic programming (CLP). In this paper, we show that 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 ACC. More interestingly, it can also leverage the inference engine for ACC which has the potential to exploit the best reasoning mechanisms developed in the ASP, SAT and CP communities.