ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Automatically synthesising domain constraints from operator descriptions
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
The computational complexity of propositional STRIPS planning
Artificial Intelligence
Temporal planning with continuous change
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Fast planning through planning graph analysis
Artificial Intelligence
Engineering and compiling planning domain models to promote validity and efficiency
Artificial Intelligence
State-variable planning under structural restrictions: algorithms and complexity
Artificial Intelligence
Inferring state constraints for domain-independent planning
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
CPlan: a constraint programming approach to planning
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Investigating the effect of relevance and reachability constraints on SAT encodings of planning
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Combining linear programming and satisfiability solving for resource planning
The Knowledge Engineering Review
Integer optimization models of AI planning problems
The Knowledge Engineering Review
Constraint partitioning in penalty formulations for solving temporal planning problems
Artificial Intelligence
On reachability, relevance, and resolution in the planning as satisfiability approach
Journal of Artificial Intelligence Research
Planning through stochastic local search and temporal action graphs in LPG
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
Temporal planning using subgoal partitioning and resolution in SGPlan
Journal of Artificial Intelligence Research
The automatic inference of state invariants in TIM
Journal of Artificial Intelligence Research
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Long-distance mutual exclusion for planning
Artificial Intelligence
Concise finite-domain representations for PDDL planning tasks
Artificial Intelligence
Learning from planner performance
Artificial Intelligence
Fast planning by search in domain transition graph
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
A weighted CSP approach to cost-optimal planning
AI Communications
Planning with action prioritization and new benchmarks for classical planning
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Planning as satisfiability with IPC simple preferences and action costs
AI Communications
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The use of mutual exclusion (mutex) has led to significant advances in propositional planning. However, previous mutex can only detect pairs of actions or facts that cannot be arranged at the same time step. In this paper, we introduce a new class of constraints that significantly generalizes mutex and can be efficiently computed. The proposed long-distance mutual exclusion (londex) can capture constraints over actions and facts not only at the same time step but also across multiple steps. Londex provides a powerful and general approach for improving planning efficiency. As an application, we have integrated londex into SATPLAN04, a leading optimal planner. Experimental results show that londex can effectively prune the search space and reduce the planning time. The resulting planner, MaxPlan, has won the First Place Award in the Optimal Track of the 5th International Planning Competition.