• Publications
  • Influence
The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks
TLDR
LAMA is a classical planning system based on heuristic forward search. Expand
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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
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A Stochastic Local Search Approach to Vertex Cover
TLDR
We introduce a novel stochastic local search algorithm for the vertex cover problem. Expand
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Natural Actor-Critic for Road Traffic Optimisation
TLDR
We use a policy-gradient reinforcement learning approach to directly optimise the traffic signals, mapping currently deployed sensor observations to control signals. Expand
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Sound and Complete Landmarks for And/Or Graphs
TLDR
We show that the complete set of causal delete-relaxation landmarks can be identified in polynomial time by a simple procedure over the relaxed planning graph, using a recently proposed admissible landmark-counting heuristic. Expand
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Lama 2008 and 2011
TLDR
LAMA is a propositional planning system based on heuristic search with landmarks, in the spirit of FF (Hoffmann and Nebel 2001) and Fast Downward. Expand
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Preferred Operators and Deferred Evaluation in Satisficing Planning
TLDR
We show that the best method for using preferred operators strongly depends on whether deferred evaluation is being employed or not in best-first search. Expand
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The LAMA Planner Using Landmark Counting in Heuristic Search
LAMA is a propositional planning system based on heuristic search. Its core feature is the use of a pseudo-heuristic derived from landmarks, propositions that must be true in every solution of aExpand
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BJOLP: The Big Joint Optimal Landmarks Planner
BJOLP, the Big Joint Optimal Landmarks Planner, uses landmarks to derive an admissible heuristic, which is then used to guide a search for a cost-optimal plan. In this paper we review landmarks andExpand
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The Joy of Forgetting: Faster Anytime Search via Restarting
TLDR
We present a new anytime approach that restarts the search from the initial state every time a new solution is found. Expand
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