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AAAI 2023

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

Conference Paper AAAI Technical Track on Knowledge Representation and Reasoning Artificial Intelligence

Abstract

In the field of parameterized complexity theory, the study of graph width measures has been intimately connected with the development of width-based model checking algorithms for combinatorial properties on graphs. 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 a polynomial of k 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.

Authors

Keywords

  • KRR: Automated Reasoning and Theorem Proving
  • KRR: Computational Complexity of Reasoning

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
457662525639425964