A new polynomial-time algorithm for linear programming
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The computational complexity of propositional STRIPS planning
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Accelerating partial-order planners: some techniques for effective search control and pruning
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STRIPS: a new approach to the application of theorem proving to problem solving
IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Fast planning through planning graph analysis
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Linear time near-optimal planning in the blocks world
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
A cost-directed planner: preliminary report
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Applying integer programming to AI planning
The Knowledge Engineering Review
Theoretical Computer Science
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Transactions on Rough Sets IX
Planning with Uncertainty in Action Outcomes as Linear Programming Problem
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Optiplan: unifying IP-based and graph-based planning
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Loosely coupled formulations for automated planning: an integer programming perspective
Journal of Artificial Intelligence Research
On the use of integer programming models in AI planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Scoring functions of approximation of STRIPS planning by linear programming
SMO'09 Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization
Reviving partial order planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Scoring functions of approximation of STRIPS planning by linear programming - block world example
WSEAS Transactions on Computers
An LP-based heuristic for optimal planning
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
On planning in multi-agent environment: algorithm of scene reasoning from incomplete information
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
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I introduce a new search heuristic for propositional STRIPS planning that is based on transforming planning instances to linear programming instances. The linear programming heuristic is admissible for finding minimum length plans and can be used by partial-order planning algorithms. This heuristic appears to be the first non-trivial admissible heuristic for partial-order planning. An empirical study compares Lplan, a partial-order planner incorporating the heuristic, to Graphplan, Satplan, and UCPOP on the tower of Hanoi domain, random blocks-world instances, and random planning instances. Graphplan is far faster in the study than the other algorithms. Lplan is often slower because the heuristic is time-consuming, but Lplan shows promise because it often perfonns a small search.