The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks

@article{Richter2010TheLP,
  title={The LAMA Planner: Guiding Cost-Based Anytime Planning with Landmarks},
  author={Silvia Richter and Matthias Westphal},
  journal={ArXiv},
  year={2010},
  volume={abs/1401.3839}
}
LAMA is a classical planning system based on heuristic forward search. [] Key Method The latter is employed to combine the landmark heuristic with a variant of the well-known FF heuristic. Both heuristics are cost-sensitive, focusing on high-quality solutions in the case where actions have non-uniform cost. A weighted A* search is used with iteratively decreasing weights, so that the planner continues to search for plans of better quality until the search is terminated. LAMA showed best performance among…
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623 Citations
Highly Influential Citations
108
Background Citations
251
Methods Citations
302
Results Citations
10

623 Citations

Citation Type

Citation Type

Lama 2008 and 2011
TLDR
Two versions of LAMA are described: the original LAMA as developed for the 2008 competition and a new re-implementation that uses the latest version of the Fast Downward Planning Framework.
Improving Plan Quality through Heuristics for Guiding and Pruning the Search: A Study Using LAMA
TLDR
The empirical results show that the use of admissible heuristics in LAMA can be of great help to improve the planner performance.
An Admissible Heuristic for SAS+ Planning Obtained from the State Equation
TLDR
A new admissible heuristic is obtained from the state equation associated to the Petri-net representation of the planning problem that can be computed in polynomial time and is competitive with the current state of the art for optimal planning, as empirically demonstrated over a large number of problems.
Better Time Constrained Search via Randomization and Postprocessing
TLDR
By using the use of restarts, randomization, and not bounding as strictly as is done by previous approaches, the new anytime search framework of Diverse Any-Time Search is able to generate a more diverse set of "raw" input plans for the post-processor to work on.
Solving Planning Problems with LRTA*
TLDR
The authors propose to replace the use of EHC and BFS with LRTA*, which is a search algorithm guided by heuristics and is as complete as BFS, and implemented some optimizations on LRTA, which shows significant improvements compared to the standard form of the FF planner.
Generating Plans Using LRTA
TLDR
A new planning method based on LRTA is presented, which is an algorithm guided by heuristics like EHC and is complete as BFS and has some optimizations like pruning successors during expansion and a heap with maximum capacity to store the states during the search.
On the Use of Landmarks in LPG
TLDR
This work proposes the use of Landmarks for the LPG planner, considering different design choices and analysing empirically its impact on the performance of the planner, finding results comparable with the state-of-the-art planner LAMA.
Width-based Algorithms for Classical Planning: New Results
TLDR
Two simple extension to Iterated Width and Serialized IW are introduced that narrow the performance gap with state-of-the-art planners.
Parallel heuristic search in forward partial-order planning
TLDR
Experimental results show that FLAP2 presents a very acceptable trade-off between time and quality and a high coverage on the current planning benchmarks, compared with four state-of-the-art planners.
Scaling-up Generalized Planning as Heuristic Search with Landmarks
TLDR
A landmark counting heuristic for GP (that considers sub-goal in- formation that is not explicitly represented in the planning in-stances), and a novel heuristic search algorithm for GP and that progressively processes subsets of the planning instances of a GP problem.
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References

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