Complexity results for standard benchmark domains in planning

  title={Complexity results for standard benchmark domains in planning},
  author={Malte Helmert},
  journal={Artif. Intell.},
  • M. Helmert
  • Published 1 February 2003
  • Computer Science
  • Artif. Intell.

Where 'Ignoring Delete Lists' Works: Local Search Topology in Planning Benchmarks

The overall investigation gives a rare example of a successful analysis of the connections between typical-case problem structure, and search performance, and gives hints on how the topological phenomena might be automatically recognizable by domain analysis techniques.

Effective Search Techniques for Non-classical Planning via Reformulation

This thesis shows that many of the most successful advances in classical planning can be leveraged for solving compelling non-classical problems, and shows that both the problems of planning with temporally extended goals and with procedural control can be mapped into classical planning.

Where Ignoring Delete Lists Works: Local Search Topology in Planning Benchmarks

Investigating a large range of planning domains, it is proved that FF's search algorithm, using an idealized heuristic function, is a polynomial solving mechanism in (at least) eleven commonly used benchmark domains.

New Complexity Results for Classical Planning Benchmarks

Complex results for the decision problems related to finding some plan, finding an optimal sequential plan, and finding a optimal parallel plan in these planning domains are proved.

Solving Simple Planning Problems with More Inference and No Search

It is shown for the first time that Blocks, Logistics, Gripper, Satellite and several other benchmark domains can be solved with no backtracks while performing only polynomial node operations, suggesting that the classes of problems that are solvable without search may be actually much broader than the classes that have been identified so far by work in Tractable Planning.

Automatic Configuration of Benchmark Sets for Classical Planning

An automated method is proposed for creating benchmarks that automatically configure the parameters of benchmark domains and shows that the resulting benchmark set improves empirical comparisons by allowing to differentiate between planners more easily.

Engineering Benchmarks for Planning: the Domains Used in the Deterministic Part of IPC-4

The article explains and discusses the five application domains and their adaptation to form the PDDL test suites used in IPC-4, and summarizes known theoretical results on structural properties of the domains, regarding their computational complexity and provable properties of their topology under the h+ function.

Optimizing Plans through Analysis of Action Dependencies and Independencies

A method is proposed for optimizing plans with respect to their length, by post-planning analysis based on analyzing action dependencies and independencies by which it is able to identify redundant actions or non-optimal sub-plans.

A weighted CSP approach to cost-optimal planning

An optimal-cost planner which guarantees global optimality whenever the planning problem has a solution is described, and the notions of indispensable (sets of) actions and too-costly actions introduced have various potential applications in optimal planning.



The 1998 AI Planning Systems Competition

The 1998 Planning Competition at the AI Planning Systems Conference was the first of its kind to create planning domains that a wide variety of planning researchers could agree on to make comparison among planners more meaningful, and set up a framework for long-term creation of a repository of problems in a standard notation.

Near-Optimal Plans, Tractability, and Reactivity

Blocks World revisited

On the Complexity of Blocks-World Planning

Automatic Synthesis and Use of Generic Types in Planning

An interesting property of the work described here is that domain components which would not easily be recognised, by the human, as transportation problems can turn out to have an underlying transportation character which can be exploited by the application of standard transportation domain heuristics.


This article provides a complete map over the complexity of SAS+ planning under all combinations of the previously considered restrictions and proves that the SAS+‐PUS problem is the maximal tractable problem under the restrictions.

AIPS 2000 Planning Competition: The Fifth International Conference on Artificial Intelligence Planning and Scheduling Systems

An overview of the AIPS'00 planning competition is presented and the main results are reviewed.

The FF Planning System: Fast Plan Generation Through Heuristic Search

A novel search strategy is introduced that combines hill-climbing with systematic search, and it is shown how other powerful heuristic information can be extracted and used to prune the search space.

Local Search Topology in Planning Benchmarks: An Empirical Analysis

Looking at a collection of planning benchmarks, the results suggest that, given the heuristic based on the relaxation, many planning benchmarks are simple in structure, shedding light on the recent success of heuristic planners employing local search.