From Width-Based Model Checking to Width-Based Automated Theorem Proving

Authors: Mateus de Oliveira Oliveira, Farhad Vadiee

AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this work, we introduce a general framework to convert a large class of width-based model-checking algorithms into algorithms that can be used to test the validity of graph-theoretic conjectures on classes of graphs of bounded width. Our framework is modular and can be applied with respect to several well-studied width measures for graphs, including treewidth and cliquewidth. As a quantitative application of our framework, we prove analytically that for several long-standing graph-theoretic conjectures, there exists an algorithm that takes a number k as input and correctly determines in time double-exponential in k O(1) whether the conjecture is valid on all graphs of treewidth at most k. These upper bounds, which may be regarded as upper-bounds on the size of proofs/disproofs for these conjectures on the class of graphs of treewidth at most k, improve significantly on theoretical upper bounds obtained using previously available techniques.
Researcher Affiliation Academia Mateus de Oliveira Oliveira1,2, Farhad Vadiee2 1 Department of Computer and System Sciences, Stockholm University, Stockholm, Sweden 2 Department of Informatics, University of Bergen, Bergen, Norway
Pseudocode No The paper does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide concrete access to source code for the methodology described.
Open Datasets No The paper is theoretical and does not conduct experiments with datasets, so it does not specify public availability of training data.
Dataset Splits No The paper is theoretical and does not conduct experiments with datasets, so it does not provide dataset splits.
Hardware Specification No The paper is theoretical and does not describe experimental procedures that would require hardware specifications.
Software Dependencies No The paper is theoretical and does not describe experimental procedures that would require software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe experimental setups, hyperparameters, or training configurations.