The computational complexity of propositional STRIPS planning
Artificial Intelligence
Planning control rules for reactive agents
Artificial Intelligence
Action versus State based Logics for Transition Systems
Proceedings of the LITP Spring School on Theoretical Computer Science: Semantics of Systems of Concurrent Processes
Planning via Model Checking: A Decision Procedure for AR
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Strong Cyclic Planning Revisited
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Design and Synthesis of Synchronization Skeletons Using Branching-Time Temporal Logic
Logic of Programs, Workshop
Planning with a language for extended goals
Eighteenth national conference on Artificial intelligence
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
A logic-based agent that plans for extended reachability goals
Autonomous Agents and Multi-Agent Systems
Symbolic Model Checking of Logics with Actions
Model Checking and Artificial Intelligence
Goal specification, non-determinism and quantifying over policies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Decision-theoretic planning with non-Markovian rewards
Journal of Artificial Intelligence Research
Planning as model checking for extended goals in non-deterministic domains
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Planning for temporally extended goals
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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The temporal logic ctl has been the preferred specificationlanguage in the model checking framework. However, when thisframework is used for nondeterministic planning, it is not adequateto deal with many useful planning problems with temporally extendedgoals. This is because the validity of ctl formulas expressing suchgoals is not evaluated on the planning domain, but on the executionstructure of the policy synthesized by the planning algorithm. Inprevious work we have presented a new variant of ctl, namedαctl, which semantics can be defined directly onthe planning domain. An advantage of this new logic is that plansynthesis can be obtained as a collateral effect of verifying thevalidity of a formula in the planning domain. In this paper we showhow to use α-ctl to express some complex planninggoals.