Probabilistic Satisfiability and Coherence Checking through Integer Programming

Fábio Gagliardi Cozman, Lucas Fargoni di Ianni

Abstract: This paper presents algorithms based on integer programming, both for probabilistic satisfiability and coherence checking. That is, we consider probabilistic assessments for both standard probability measures (Kolmogorovian setup) and full conditional measures (de Finettian coherence setup), and in both cases verify satisfiability/coherence using integer programming. We present empirical evaluation of our method, with evidence of phase-transitions.