Incremental Symmetry Breaking Constraints for Graph Search Problems

Authors: Avraham Itzhakov, Michael Codish1536-1543

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We demonstrate our approach through its application on two hard graph search problems.
Researcher Affiliation Academia Avraham Itzhakov, Michael Codish Department of Computer Science Ben-Gurion University of the Negev {itzhakoa, mcodish}@cs.bgu.ac.il
Pseudocode Yes Algorithm 1 Compute a compact complete symmetry break for X {R, C}, Y {lex, imp}
Open Source Code Yes The symmetry breaking constraints described in this paper can be obtained from www. cs.bgu.ac.il/ mcodish/Papers/Tools/incremental SBC.
Open Datasets No The paper focuses on graph search problems and enumerating objects with certain properties, which does not involve traditional machine learning training datasets. No specific training dataset is mentioned.
Dataset Splits No The paper describes a graph search and enumeration problem, not a machine learning task that utilizes validation datasets. No dataset splits for validation are mentioned.
Hardware Specification Yes All computations were performed on a cluster of servers, each with 56 Intel Xeon E5-2620 cores and 256GB of RAM memory, clocked at 2 GHz.
Software Dependencies Yes The computations described in this paper are performed using the finite-domain constraint compiler BEE (Metodi, Codish, and Stuckey 2013) which compiles constraints to a CNF, and solves it applying an underlying SAT solver (we use Glucose 4.0 (Audemard and Simon )).
Experiment Setup Yes Each SAT instance is run on a single thread. We impose a 24 hour timeout on each instance.