Phase Transition Behavior in Knowledge Compilation
Rahul Gupta, Subhajit Roy, Kuldeep S. Meel

TL;DR
This paper empirically investigates the phase transition behavior in knowledge compilation for random k-CNF formulas, analyzing size and runtime across different compilation methods and identifying key parameters influencing complexity.
Contribution
It introduces a comprehensive empirical analysis of phase transition phenomena in knowledge compilation, highlighting the roles of clause and solution densities.
Findings
Size and runtime exhibit phase transition behavior influenced by clause and solution densities.
Identification of a novel control parameter, solution density, affecting compilation complexity.
Formulation of two conjectures guiding future theoretical research.
Abstract
The study of phase transition behaviour in SAT has led to deeper understanding and algorithmic improvements of modern SAT solvers. Motivated by these prior studies of phase transitions in SAT, we seek to study the behaviour of size and compile-time behaviour for random k-CNF formulas in the context of knowledge compilation. We perform a rigorous empirical study and analysis of the size and runtime behavior for different knowledge compilation forms (and their corresponding compilation algorithms): d-DNNFs, SDDs and OBDDs across multiple tools and compilation algorithms. We employ instances generated from the random k-CNF model with varying generation parameters to empirically reason about the expected and median behavior of size and compilation-time for these languages. Our work is similar in spirit to the early work in CSP community on phase transition behavior in SAT/CSP. In a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
