Succinct representations of graphs
Information and Control
Macro-operators: a weak method for learning
Artificial Intelligence - Lecture notes in computer science 178
Planning as search: a quantitative approach
Artificial Intelligence
On generating all maximal independent sets
Information Processing Letters
Planning in polynomial time: the SAS-PUBS class
Computational Intelligence
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
The computational complexity of propositional STRIPS planning
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Expressive equivalence of planning formalisms
Artificial Intelligence - Special volume on planning and scheduling
Plan reuse versus plan generation: a theoretical and empirical analysis
Artificial Intelligence - Special volume on planning and scheduling
The complexity of searching implicit graphs
Artificial Intelligence
State-variable planning under structural restrictions: algorithms and complexity
Artificial Intelligence
Remote Agent: to boldly go where no AI system has gone before
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Towards efficient universal planning: a randomized approach
Artificial Intelligence
Using temporal logics to express search control knowledge for planning
Artificial Intelligence
New applications of the incompressibility method: part II
Theoretical Computer Science - Selected papers in honor of Manuel Blum
Generating Abstraction Hierarchies: An Automated Approach to Reducing Search in Planning
Generating Abstraction Hierarchies: An Automated Approach to Reducing Search in Planning
Applied Algebra for the Computer Sciences
Applied Algebra for the Computer Sciences
A Survey on Case-Based Planning
Artificial Intelligence Review
Tractable plan existence does not imply tractable plan generation
Annals of Mathematics and Artificial Intelligence
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Some connections between nonuniform and uniform complexity classes
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Application of Lempel--Ziv factorization to the approximation of grammar-based compression
Theoretical Computer Science
A Simple Algorithm for Mal'tsev Constraints
SIAM Journal on Computing
Assessing the complexity of plan recognition
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The Causal Graph Revisited for Directed Model Checking
SAS '09 Proceedings of the 16th International Symposium on Static Analysis
On the compilability and expressive power of propositional planning formalisms
Journal of Artificial Intelligence Research
Space efficiency of propositional knowledge representation formalisms
Journal of Artificial Intelligence Research
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
The complexity of planning problems with simple causal graphs
Journal of Artificial Intelligence Research
Planning with abstraction hierarchies can be exponentially less efficient
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Conformant plans and beyond: Principles and complexity
Artificial Intelligence
The role of macros in tractable planning
Journal of Artificial Intelligence Research
Causal graphs and structurally restricted planning
Journal of Computer and System Sciences
Computing optimal policies for partially observable decision processes using compact representations
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Random access to grammar-compressed strings
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
IEEE Transactions on Information Theory
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Compact representations of objects is a common concept in computer science. Automated planning can be viewed as a case of this concept: a planning instance is a compact implicit representation of a graph and the problem is to find a path (a plan) in this graph. While the graphs themselves are represented compactly as planning instances, the paths are usually represented explicitly as sequences of actions. Some cases are known where the plans always have compact representations, for example, using macros. We show that these results do not extend to the general case, by proving a number of bounds for compact representations of plans under various criteria, like efficient sequential or random access of actions. In addition to this, we show that our results have consequences for what can be gained from reformulating planning into some other problem. As a contrast to this we also prove a number of positive results, demonstrating restricted cases where plans do have useful compact representations, as well as proving that macro plans have favourable access properties. Our results are finally discussed in relation to other relevant contexts.