Planning for conjunctive goals
Artificial Intelligence
Introduction to algorithms
Reasoning about plans
Planning in polynomial time: the SAS-PUBS class
Computational Intelligence
The computational complexity of propositional STRIPS planning
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Downward refinement and the efficiency of hierarchical problem solving
Artificial Intelligence
Complexity, decidability and undecidability results for domain-independent planning
Artificial Intelligence - Special volume on planning and scheduling
GPS, a program that simulates human thought
Computers & thought
New directions in AI planning
State-variable planning under structural restrictions: algorithms and complexity
Artificial Intelligence
Artificial Intelligence - Special issue on heuristic search in artificial intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Tractable plan existence does not imply tractable plan generation
Annals of Mathematics and Artificial Intelligence
Complexity results for standard benchmark domains in planning
Artificial Intelligence
Constraint Processing
Utilizing Problem Structure in Planning: A Local Search Approach
Utilizing Problem Structure in Planning: A Local Search Approach
Factored planning: how, when, and when not
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
New admissible heuristics for domain-independent planning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
A reactive planner for a model-based executive
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
The FF planning system: fast plan generation through heuristic search
Journal of Artificial Intelligence Research
Structure and complexity in planning with unary operators
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
The deterministic part of IPC-4: an overview
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
Admissible pruning strategies based on plan minimality for plan-space planning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A model-based approach to reactive self-configuring systems
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Planning over chain causal graphs for variables with domains of size 5 Is NP-hard
Journal of Artificial Intelligence Research
The role of macros in tractable planning
Journal of Artificial Intelligence Research
Optimal admissible composition of abstraction heuristics
Artificial Intelligence
Analyzing search topology without running any search: on the connection between causal graphs and h+
Journal of Artificial Intelligence Research
The influence of k-dependence on the complexity of planning
Artificial Intelligence
Implicit abstraction heuristics for cost-optimal planning
AI Communications
On the complexity of planning for agent teams and its implications for single agent planning
Artificial Intelligence
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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We study the complexity of cost-optimal classical planning over propositional state variables and unary-effect actions. We discover novel problem fragments for which such optimization is tractable, and identify certain conditions that differentiate between tractable and intractable problems. These results are based on exploiting both structural and syntactic characteristics of planning problems. Specifically, following Brafman and Domshlak (2003), we relate the complexity of planning and the topology of the causal graph. The main results correspond to tractability of cost-optimal planning for propositional problems with polytree causal graphs that either have O(1)-bounded in-degree, or are induced by actions having at most one prevail condition each. Almost all our tractability results are based on a constructive proof technique that connects between certain tools from planning and tractable constraint optimization, and we believe this technique is of interest on its own due to a clear evidence for its robustness.