Random Constraint Satisfaction Problems (CSPs) are ubiquitous in computer science and everyday life, including examples ranging from Sudokus to optimal digital board design. A CSP involves many discrete variables interacting through random constraints. When the number of competing conditions gets large, the optimization of a CSP instance can become extraordinarily hard. The Survey Propagation algorithm, based on the iterative exchange of simple probabilistic messages along the edges of a factor graph, succeeds to optimize even very hard random instances, whereas more standard...
Random Constraint Satisfaction Problems (CSPs) are ubiquitous in computer science and everyday life, including examples ranging from Sudokus to opti...