The computational complexity of propositional STRIPS planning
Artificial Intelligence
Guarded commands, nondeterminacy and formal derivation of programs
Communications of the ACM
An axiomatic basis for computer programming
Communications of the ACM
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Weak, strong, and strong cyclic planning via symbolic model checking
Artificial Intelligence - special issue on planning with uncertainty and incomplete information
Computation: finite and infinite machines
Computation: finite and infinite machines
Termination proofs for systems code
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Learning generalized plans using abstract counting
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Merging example plans into generalized plans for non-deterministic environments
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A new representation and associated algorithms for generalized planning
Artificial Intelligence
Foundations and applications of generalized planning
Foundations and applications of generalized planning
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The utility of including loops in plans has been long recognized by the planning community. Loops in a plan help increase both its applicability and the compactness of its representation. However, progress in finding such plans has been limited largely due to lack of methods for reasoning about the correctness and safety properties of loops of actions. We present novel algorithms for determining the applicability and progress made by a general class of loops of actions. These methods can be used for directing the search for plans with loops towards greater applicability while guaranteeing termination, as well as in post-processing of computed plans to precisely characterize their applicability. Experimental results demonstrate the efficiency of these algorithms. We also discuss the factors which can make the problem of determining applicability conditions for plans with loops incomputable.