Optimal Planning for Delete-Free Tasks with Incremental LM-Cut
نویسندگان
چکیده
Optimal plans of delete-free planning tasks are interesting both in domains that have no delete effects and as the relaxation heuristic h in general planning. Many heuristics for optimal and satisficing planning approximate the h heuristic, which is well-informed and admissible but intractable to compute. In this work, branch-and-bound and IDA∗ search are used in a search space tailored to delete-free planning together with an incrementally computed version of the LMcut heuristic. The resulting algorithm for optimal delete-free planning exceeds the performance of A∗ with the LM-cut heuristic in the state-of-the-art planner Fast Downward.
منابع مشابه
On a Practical, Integer-Linear Programming Model for Delete-Free Tasks and its Use as a Heuristic for Cost-Optimal Planning
We propose a new integer-linear programming model for the delete relaxation in cost-optimal planning. While a straightforward IP for the delete relaxation is impractical, our enhanced model incorporates variable reduction techniques based on landmarks, relevance-based constraints, dominated action elimination, immediate action application, and inverse action constraints, resulting in an IP that...
متن کاملLM-Cut: Optimal Planning with the Landmark-Cut Heuristic∗
The LM-Cut planner uses the landmark-cut heuristic, introduced by the authors in 2009, within a standard A∗ progression search framework to find optimal sequential plans for STRIPS-style planning tasks. This short paper recapitulates the main ideas surrounding the landmark-cut heuristic and provides pointers for further reading.
متن کاملIncremental LM-Cut
In heuristic search and especially in optimal classical planning the computation of accurate heuristic values can take up the majority of runtime. In many cases, the heuristic computations for a search node and its successors are very similar, leading to significant duplication of effort. For example most landmarks of a node that are computed by the LM-cut algorithm are also landmarks for the n...
متن کاملComputation of h with Factored Planning
The main approach for classical planning is heuristic search. Many cost heuristics are based on the delete relaxation. The optimal heuristic of a delete free planning problem is called h. This thesis explores two new ways to compute h. Both approaches use factored planning, which decomposes the original planning problem to work on each subproblem separately. The algorithm reuses the subsolution...
متن کاملOptimal Delete-Relaxed (and Semi-Relaxed) Planning with Conditional Effects
Recently, several methods have been proposed for optimal delete-free planning. We present an incremental compilation approach that enables these methods to be applied to problems with conditional effects, which none of them support natively. With an h solver for problems with conditional effects in hand, we also consider adapting the h anytime lower bound function to use the more spaceefficient...
متن کامل