Complexity of finding embeddings in a k-tree
SIAM Journal on Algebraic and Discrete Methods
Automatically generating abstractions for planning
Artificial Intelligence
Downward refinement and the efficiency of hierarchical problem solving
Artificial Intelligence
HTN planning: complexity and expressivity
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Planning as constraint satisfaction: solving the planning graph by compiling it into CSP
Artificial Intelligence
Constraint Processing
Branching and pruning: an optimal temporal POCL planner based on constraint programming
Artificial Intelligence
A reactive planner for a model-based executive
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Structure and complexity in planning with unary operators
Journal of Artificial Intelligence Research
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Over-subscription planning with numeric goals
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Scope and abstraction: two criteria for localized planning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Pushing the envelope: planning, propositional logic, and stochastic search
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Heuristics for Planning with Action Costs Revisited
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
WoLLIC '09 Proceedings of the 16th International Workshop on Logic, Language, Information and Computation
Probabilistic planning via heuristic forward search and weighted model counting
Journal of Artificial Intelligence Research
Loosely coupled formulations for automated planning: an integer programming perspective
Journal of Artificial Intelligence Research
The complexity of planning problems with simple causal graphs
Journal of Artificial Intelligence Research
New Islands of tractability of cost-optimal planning
Journal of Artificial Intelligence Research
Planning over chain causal graphs for variables with domains of size 5 Is NP-hard
Journal of Artificial Intelligence Research
Reducing accidental complexity in planning problems
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
The role of macros in tractable planning over causal graphs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Factored planning using decomposition trees
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Completeness and optimality preserving reduction for planning
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Decomposition of Multi-player Games
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
Combining planning and motion planning
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
The role of macros in tractable planning
Journal of Artificial Intelligence Research
Understanding planning tasks: domain complexity and heuristic decomposition
Understanding planning tasks: domain complexity and heuristic decomposition
Causal graphs and structurally restricted planning
Journal of Computer and System Sciences
A general, fully distributed multi-agent planning algorithm
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
The influence of k-dependence on the complexity of planning
Artificial Intelligence
On the complexity of planning for agent teams and its implications for single agent planning
Artificial Intelligence
Generating instruction streams using abstract CSP
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Parameterized complexity of optimal planning: a detailed map
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A refined view of causal graphs and component sizes: SP-closed graph classes and beyond
Journal of Artificial Intelligence Research
The complexity of optimal monotonic planning: the bad, the good, and the causal graph
Journal of Artificial Intelligence Research
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Automated domain factoring, and planning methods that utilize them, have long been of interest to planning researchers. Recent work in this area yielded new theoretical insight and algorithms, but left many questions open: How to decompose a domain into factors? How to work with these factors? And whether and when decomposition-based methods are useful? This paper provides theoretical analysis that answers many of these questions: it proposes a novel approach to factored planning; proves its theoretical superiority over previous methods; provides insight into how to factor domains; and uses its novel complexity results to analyze when factored planning is likely to perform well, and when not. It also establishes the key role played by the domain's causal graph in the complexity analysis of planning algorithms.