The computational complexity of propositional STRIPS planning
Artificial Intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Combining the Expressivity of UCPOP with the Efficiency of Graphplan
ECP '97 Proceedings of the 4th European Conference on Planning: Recent Advances in AI Planning
On reasonable and forced goal orderings and their use in an agenda-driven planning algorithm
Journal of Artificial Intelligence Research
When gravity fails: local search topology
Journal of Artificial Intelligence Research
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
Complexity results for standard benchmark domains in planning
Artificial Intelligence
An Accurate Adaptation-Guided Similarity Metric for Case-Based Planning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
A logical measure of progress for planning
Eighteenth national conference on Artificial intelligence
SetA*: an efficient BDD-based heuristic search algorithm
Eighteenth national conference on Artificial intelligence
Sensor networks and distributed CSP: communication, computation and complexity
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Artificial Intelligence
Decomposition of planning problems
AI Communications
Domain-independent temporal planning in a planning-graph-based approach
AI Communications
Learning from planner performance
Artificial Intelligence
The FF planning system: fast plan generation through heuristic search
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
The fast downward planning system
Journal of Artificial Intelligence Research
Engineering benchmarks for planning: the domains used in the deterministic part of IPC-4
Journal of Artificial Intelligence Research
Marvin: a heuristic search planner with online macro-action learning
Journal of Artificial Intelligence Research
A critical assessment of benchmark comparison in planning
Journal of Artificial Intelligence Research
The GRT planning system: backward heuristic construction in forward state-space planning
Journal of Artificial Intelligence Research
Sensor networks and distributed CSP: communication, computation and complexity
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Understanding planning tasks: domain complexity and heuristic decomposition
Understanding planning tasks: domain complexity and heuristic decomposition
Everything you always wanted to know about planning (but were afraid to ask)
KI'11 Proceedings of the 34th Annual German conference on Advances in artificial intelligence
Controlled reachability analysis in AI planning: theory and practice
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
| Hi-index | 0.00 |
Many state-of-the-art heuristic planners derive their heuristic function by relaxing the planning task at hand, where the relaxation is to assume that all delete lists are empty. Looking at a collection of planning benchmarks, we measure topological properties of state spaces with respect to that relaxation. The results suggest that, given the heuristic based on the relaxation, many planning benchmarks are simple in structure. This sheds light on the recent success of heuristic planners employing local search.