ADL: exploring the middle ground between STRIPS and the situation calculus
Proceedings of the first international conference on Principles of knowledge representation and reasoning
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
On the complexity of blocks-world planning
Artificial Intelligence
Learning by analogical reasoning in general problem-solving
Learning by analogical reasoning in general problem-solving
Partial-order planning: evaluating possible efficiency gains
Artificial Intelligence
Fast planning through planning graph analysis
Artificial Intelligence
Engineering and compiling planning domain models to promote validity and efficiency
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
Using regression-match graphs to control search in planning
Artificial Intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Temporal Planning with Mutual Exclusion Reasoning
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
The Detection and Exploitation of Symmetry in Planning Problems
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Discovering State Constraints in DISCOPLAN: Some New Results
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Ignoring Irrelevant Facts and Operators in Plan Generation
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
Action Constraints for Planning
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
On Determining and Completeing Incomplete States in STRIPS Domains
ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
Human Problem Solving
On reasonable and forced goal orderings and their use in an agenda-driven planning algorithm
Journal of Artificial Intelligence Research
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
The automatic inference of state invariants in TIM
Journal of Artificial Intelligence Research
Efficient implementation of the plan graph in STAN
Journal of Artificial Intelligence Research
Hybrid STAN: Identifying and managing combinatorial optimisation sub-problems in planning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Local search topology in planning benchmarks: an empirical analysis
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Fast planning through planning graph analysis
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Finding optimal solutions to the twenty-four puzzle
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Linear time near-optimal planning in the blocks world
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
Speeding up the calculation of heuristics for heuristic search-based planning
Eighteenth national conference on Artificial intelligence
Multiobjective heuristic state-space planning
Artificial Intelligence
HAPRC: an automatically configurable planning system
AI Communications
Decomposition of planning problems
AI Communications
Heuristic Hill-Climbing as a Markov Process
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
State agnostic planning graphs and the application to belief-space planning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Finding state similarities for faster planning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Sapa: a multi-objective metric temporal planner
Journal of Artificial Intelligence Research
The metric-FF planning system: translating "Ignoring delete lists" to numeric state variables
Journal of Artificial Intelligence Research
VHPOP: versatile heuristic partial order planner
Journal of Artificial Intelligence Research
Where "Ignoring delete lists" works: local search topology in planning benchmarks
Journal of Artificial Intelligence Research
Planning via Petri net unfolding
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Set-structured and cost-sharing heuristics for classical planning
Annals of Mathematics and Artificial Intelligence
State agnostic planning graphs: deterministic, non-deterministic, and probabilistic planning
Artificial Intelligence
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This paper presents GRT, a domain-independent heuristic planning system for STRIPS worlds. GRT solves problems in two phases. In the pre-processing phase, it estimates the distance between each fact and the goals of the problem, in a backward direction. Then, in the search phase, these estimates are used in order to further estimate the distance between each intermediate state and the goals, guiding so the search process in a forward direction and on a best-first basis. The paper presents the benefits from the adoption of opposite directions between the preprocessing and the search phases, discusses some difficulties that arise in the pre-processing phase and introduces techniques to cope with them. Moreover, it presents several methods of improving the efficiency of the heuristic, by enriching the representation and by reducing the size of the problem. Finally, a method of overcoming local optimal states, based on domain axioms, is proposed. According to it, difficult problems are decomposed into easier sub-problems that have to be solved sequentially. The performance results from various domains, including those of the recent planning competitions, show that GRT is among the fastest planners.