The cavity method: from exact solutions to algorithms

09/23/2022

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The goal of this chapter is to review the main ideas that underlie the cavity method for disordered models defined on random graphs, as well as present some of its outcomes, focusing on the random constraint satisfaction problems for which it provided both a better understanding of the phase transitions they undergo, and suggestions for the development of algorithms to solve them.

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The cavity method: from exact solutions to algorithms

Exact Phase Transitions in Random Constraint Satisfaction Problems

Counting Solutions of Constraint Satisfiability Problems:Exact Phase Transitions and Approximate Algorithm

Exact Phase Transitions of Model RB with Slower-Growing Domains

The replica symmetric phase of random constraint satisfaction problems

The asymptotics of the clustering transition for random constraint satisfaction problems

Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference

AFSCR: Annotation of Functional Satisfaction Conditions and their Reconciliation within i* models

The cavity method: from exact solutions to algorithms

Related Research

Exact Phase Transitions in Random Constraint Satisfaction Problems

Counting Solutions of Constraint Satisfiability Problems:Exact Phase Transitions and Approximate Algorithm

Exact Phase Transitions of Model RB with Slower-Growing Domains

The replica symmetric phase of random constraint satisfaction problems

The asymptotics of the clustering transition for random constraint satisfaction problems

Phase Transition of Tractability in Constraint Satisfaction and Bayesian Network Inference

AFSCR: Annotation of Functional Satisfaction Conditions and their Reconciliation within i* models