• Publications
  • Influence
The Fast Downward Planning System
  • M. Helmert
  • Computer Science, Mathematics
  • J. Artif. Intell. Res.
  • 1 May 2006
TLDR
Fast Downward is a classical planning system based on heuristic search. Expand
Landmarks, Critical Paths and Abstractions: What's the Difference Anyway?
TLDR
We introduce a new admissible heuristic called the landmark cut heuristic, which compares favourably with the state of the art in terms of heuristic accuracy and overall performance. Expand
Landmarks Revisited
TLDR
We propose a novel approach for using landmarks in planning by deriving a pseudo-heuristic and combining it with other heuristics in a search framework, and our novel use of landmarks during search solves more planning tasks and delivers considerably better solutions. Expand
Concise finite-domain representations for PDDL planning tasks
  • M. Helmert
  • Computer Science
  • Artif. Intell.
  • 1 April 2009
TLDR
We introduce an efficient method for translating planning tasks specified in the standard PDDL formalism into a concise grounded representation that uses finite-domain state variables instead of the straight-forward propositional encoding. Expand
Flexible Abstraction Heuristics for Optimal Sequential Planning
TLDR
We describe an approach to deriving consistent heuristics for automated planning, based on explicit search in abstract state spaces. Expand
A Planning Heuristic Based on Causal Graph Analysis
TLDR
We propose translating STRIPS problems to a planning formalism with multi-valued state variables in order to expose the underlying causal structure of the domain, which is evident to humans. Expand
Domain-Independent Construction of Pattern Database Heuristics for Cost-Optimal Planning
TLDR
We present a novel way of constructing good patterns automatically from the specification of planning problem instances. Expand
A Stochastic Local Search Approach to Vertex Cover
TLDR
We introduce a novel stochastic local search algorithm for the vertex cover problem. Expand
Merge-and-Shrink Abstraction
TLDR
We show that merge-and-shrink abstraction is a new paradigm that, as we show, allows to compactly represent a more general class of abstractions, strictly dominating pattern databases in theory. Expand
Complexity results for standard benchmark domains in planning
  • M. Helmert
  • Computer Science
  • Artif. Intell.
  • 1 February 2003
TLDR
We define and analyze a general transportation problem that generalizes planning in several classical domains such as LOGISTICS, MYSTERY and GRIPPER. Expand
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