Generalized probabilistic satisfiability through integer programming

被引：0

作者：

Bona, Glauber De ^{[1
]}

Cozman, Fabio G. ^{[2
]}

Finger, Marcelo ^{[1
]}

机构：

[1] Instituto de Matemática e Estatística, Universidade de São Paulo, Rua do Matão 1010, Sao Paulo, Brazil

[2] Escola Politécnica, Universidade de São Paulo, Avenida Professor Luciano Gualberto 380, Sao Paulo, Brazil

来源：

Journal of the Brazilian Computer Society | 2015年 / 21卷 / 01期

关键词：

Boolean combinations - Integer Linear Programming - Mixed integer linear programming - Multi agent - Normal form - Phase transition phenomenon - Satisfiability;

D O I：

10.1186/s13173-015-0028-x

中图分类号：

学科分类号：

摘要：

Background: This paper studies the generalized probabilistic satisfiability (GPSAT) problem, where the probabilistic satisfiability (PSAT) problem is extended by allowing Boolean combinations of probabilistic assertions and nested probabilistic formulas. Methods: We introduce a normal form for this problem and show that both nesting of probabilities and multi-agent probabilities do not increase the expressivity of GPSAT. An algorithm to solve GPSAT instances in the normal form via mixed integer linear programming is proposed. Results: The implementation of the algorithm is used to explore the complexity profile of GPSAT, and it shows evidence of phase-transition phenomena. Conclusions: Even though GPSAT is considerably more expressive than PSAT, it can be handled using integer linear programming techniques. © 2015, De Bona et al.

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