Generality in artificial intelligence
Communications of the ACM
HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
Event Calculus Planning Revisited
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
A modular action description language
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Planning in a hierarchy of abstraction spaces
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
Embracing causality in specifying the indirect effects of actions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Developing high-level cognitive functions for service robots
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
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This paper extends action language $\mathcal{C}+$ by introducing composite actions as sequential execution of primitive actions. Such extension leads to a more intuitive and flexible way to represent action domains, better exploit a general-purpose formalization, and improve the reasoning efficiency for large domains. The semantics of composite actions is defined by a translation to nonmonotonic causal theories. We implement the language by extending cplus2asp, which translates causal theories into answer set programming (ASP) and calls ASP solver.