Symmetry Breaking for Answer Set Programming
Christian Drescher

TL;DR
This paper presents automated symmetry detection and breaking techniques for answer set programming, reducing search space and improving solver efficiency, with applications to constraint satisfaction and distributed systems.
Contribution
It introduces a graph automorphism-based symmetry detection method, an encoding of symmetry-breaking constraints, and applies these to various answer set programming domains.
Findings
Significant computational improvements on benchmark problems.
Effective symmetry breaking in constraint answer set programming.
Distributed symmetry detection algorithms developed.
Abstract
In the context of answer set programming, this work investigates symmetry detection and symmetry breaking to eliminate symmetric parts of the search space and, thereby, simplify the solution process. We contribute a reduction of symmetry detection to a graph automorphism problem which allows to extract symmetries of a logic program from the symmetries of the constructed coloured graph. We also propose an encoding of symmetry-breaking constraints in terms of permutation cycles and use only generators in this process which implicitly represent symmetries and always with exponential compression. These ideas are formulated as preprocessing and implemented in a completely automated flow that first detects symmetries from a given answer set program, adds symmetry-breaking constraints, and can be applied to any existing answer set solver. We demonstrate computational impact on benchmarks…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Multi-Agent Systems and Negotiation · Bayesian Modeling and Causal Inference
