The computational complexity of propositional STRIPS planning
Artificial Intelligence
Fast planning through planning graph analysis
Artificial Intelligence
Extending Planning Graphs to an ADL Subset
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Ignoring Irrelevant Facts and Operators in Plan Generation
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Planning as Heuristic Search: New Results
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
GRT: A Domain Independent Heuristic for STRIPS Worlds Based on Greedy Regression Tables
ECP '99 Proceedings of the 5th European Conference on Planning: Recent Advances in AI Planning
Efficient implementation of the plan graph in STAN
Journal of Artificial Intelligence Research
Unifying SAT-based and graph-based planning
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
A robust and fast action selection mechanism for planning
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A Heuristic for Planning Based on Action Evaluation
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Combining reinforcement learning with symbolic planning
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Case-based subgoaling in real-time heuristic search for video game pathfinding
Journal of Artificial Intelligence Research
BioDKM: Bio-inspired domain knowledge modeling method for humanoid delivery robots' planning
Expert Systems with Applications: An International Journal
Application of fixed-structure genetic programming for classification
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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We present a new heuristic method to evaluate planning states, which is based on solving a relaxation of the planning problem. The solutions to the relaxed problem give a good estimate for the length of a real solution, and they can also be used to guide action selection during planning. Using these informations, we employ a search strategy that combines Hill-climbing with systematic search. The algorithm is complete on what we call deadlock-free domains. Though it does not guarantee the solution plans to be optimal, it does find close to optimal plans in most cases. Often, it solves the problems almost without any search at all. In particular, it outperforms all state-of-the-art planners on a large range of domains.