The computational complexity of propositional STRIPS planning
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Fixed-parameter tractability and completeness II: on completeness for W[1]
Theoretical Computer Science
A comparison of structural CSP decomposition methods
Artificial Intelligence
Tractable plan existence does not imply tractable plan generation
Annals of Mathematics and Artificial Intelligence
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
The complexity of homomorphism and constraint satisfaction problems seen from the other side
Journal of the ACM (JACM)
Factored planning: how, when, and when not
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Structure and complexity in planning with unary operators
Journal of Artificial Intelligence Research
The fast downward planning system
Journal of Artificial Intelligence Research
The complexity of planning problems with simple causal graphs
Journal of Artificial Intelligence Research
The role of macros in tractable planning over causal graphs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Analyzing search topology without running any search: on the connection between causal graphs and h+
Journal of Artificial Intelligence Research
Algorithms and limits for compact plan representations
Journal of Artificial Intelligence Research
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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The causal graph is a directed graph that describes the variable dependencies present in a planning instance. A number of papers have studied the causal graph in both practical and theoretical settings. In this work, we systematically study the complexity of planning restricted by the causal graph. In particular, any set of causal graphs gives rise to a subcase of the planning problem. We give a complete classification theorem on causal graphs, showing that a set of graphs is either polynomial-time tractable, or is not polynomial-time tractable unless an established complexity-theoretic assumption fails; our theorem describes which graph sets correspond to each of the two cases. We also give a classification theorem for the case of reversible planning, and discuss the general direction of structurally restricted planning.