Planning for conjunctive goals
Artificial Intelligence
Planning as search: a quantitative approach
Artificial Intelligence
Introduction to algorithms
The computational complexity of propositional STRIPS planning
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Complexity, decidability and undecidability results for domain-independent planning
Artificial Intelligence - Special volume on planning and scheduling
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
Factored planning: how, when, and when not
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
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
Journal of Artificial Intelligence Research
Macro-FF: improving AI planning with automatically learned macro-operators
Journal of Artificial Intelligence Research
The fast downward planning system
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
The role of macros in tractable planning
Journal of Artificial Intelligence Research
Causal graphs and structurally restricted planning
Journal of Computer and System Sciences
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
Algorithms and limits for compact plan representations
Journal of Artificial Intelligence Research
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
Limitations of acyclic causal graphs for planning
Artificial Intelligence
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We present three new complexity results for classes of planning problems with simple causal graphs. First, we describe a polynomial-time algorithm that uses macros to generate plans for the class 3S of planning problems with binary state variables and acyclic causal graphs. This implies that plan generation may be tractable even when a planning problem has an exponentially long minimal solution. We also prove that the problem of plan existence for planning problems with multi-valued variables and chain causal graphs is NP-hard. Finally, we show that plan existence for planning problems with binary state variables and polytree causal graphs is NP-complete.