AIPLSep 17, 2021

Modeling and Solving Graph Synthesis Problems Using SAT-Encoded Reachability Constraints in Picat

arXiv:2109.08293v12 citations
Originality Synthesis-oriented
AI Analysis

This work addresses constraint satisfaction problems for researchers and practitioners in logic programming and constraint solving, but it is incremental as it applies existing methods to new data.

The paper tackled graph synthesis problems with reachability constraints by developing Picat programs for four competition problems, demonstrating the language's modeling capabilities and the efficiency of SAT solvers with effective encodings.

Many constraint satisfaction problems involve synthesizing subgraphs that satisfy certain reachability constraints. This paper presents programs in Picat for four problems selected from the recent LP/CP programming competitions. The programs demonstrate the modeling capabilities of the Picat language and the solving efficiency of the cutting-edge SAT solvers empowered with effective encodings.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes