mlsanityData to 7 Oct 2026

Representation and Synthesis of C++ Programs for Generalized Planning

arXiv 2206.14480 ↗First posted 29 Jun 2022cs.AIcited by 1

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Abstract (arXiv)

The paper introduces a novel representation for Generalized Planning (GP) problems, and their solutions, as C++ programs. Our C++ representation allows to formally proving the termination of generalized plans, and to specifying their asymptotic complexity w.r.t. the number of world objects. Characterizing the complexity of C++ generalized plans enables the application of a combinatorial search that enumerates the space of possible GP solutions in order of complexity. Experimental results show that our implementation of this approach, which we call BFGP++, outperforms the previous GP as heuristic search approach for the computation of generalized plans represented as compiler-styled programs. Last but not least, the execution of a C++ program on a classical planning instance is a deterministic grounding-free and search-free process, so our C++ representation allows us to automatically validate the computed solutions on large test instances of thousands of objects, where off-the-shelf classical planners get stuck either in the pre-processing or in the search.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 51 references that are in the map. First posted on arXiv 29 Jun 2022.

Builds on

5 of 51 references.

References · 5

  1. 2021Generalized Planning as Heuristic Searchcited by 18
  2. 2022Scaling-up Generalized Planning as Heuristic Search with Landmarkscited by 14
  3. 2021Learning General Policies from Small Examples Without Supervisioncited by 7
  4. 2019Generalized Planning with Positive and Negative Examplescited by 5
  5. 2022Computing Programs for Generalized Planning as Heuristic Searchcited by 3

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Citing papers per year: 2023: 1.

1 paper.