Solving Constraint Satisfaction Problems through Belief Propagation-guided decimation

@misc{citeulike:1647432, abstract = {Message passing algorithms have proved surprisingly successful in solving hard constraint satisfaction problems on sparse random graphs. In such applications, variables are fixed sequentially to satisfy the constraints. Message passing is run after each step. Its outcome provides an heuristic to make choices at next step. This approach has been referred to as `decimation,' with reference to analogous procedures in statistical physics. The behavior of decimation procedures is poorly understood. Here we consider a simple randomized decimation algorithm based on belief propagation (BP), and analyze its behavior on random k-satisfiability formulae. In particular, we propose a tree model for its analysis and we conjecture that it provides asymptotically exact predictions in the limit of large instances. This conjecture is confirmed by numerical simulations.}, author = {Montanari, Andrea and Ricci-Tersenghi, Federico and Semerjian, Guilhem }, citeulike-article-id = {1647432}, eprint = {0709.1667}, keywords = {bp, coding-theory, lp, random-sat, sat}, month = {Sep}, posted-at = {2007-09-12 21:50:26}, priority = {2}, title = {Solving Constraint Satisfaction Problems through Belief Propagation-guided decimation}, url = {http://arxiv.org/abs/0709.1667}, year = {2007} }

TY - ELEC ID - citeulike:1647432 L3 - citeulike-article-id:1647432 TI - Solving Constraint Satisfaction Problems through Belief Propagation-guided decimation N2 - Message passing algorithms have proved surprisingly successful in solving hard constraint satisfaction problems on sparse random graphs. In such applications, variables are fixed sequentially to satisfy the constraints. Message passing is run after each step. Its outcome provides an heuristic to make choices at next step. This approach has been referred to as `decimation,' with reference to analogous procedures in statistical physics. The behavior of decimation procedures is poorly understood. Here we consider a simple randomized decimation algorithm based on belief propagation (BP), and analyze its behavior on random k-satisfiability formulae. In particular, we propose a tree model for its analysis and we conjecture that it provides asymptotically exact predictions in the limit of large instances. This conjecture is confirmed by numerical simulations. KW - bp KW - coding-theory KW - lp KW - random-sat KW - sat AU - Montanari, Andrea AU - Ricci-Tersenghi, Federico AU - Semerjian, Guilhem PY - 2007/Sep/11/ UR - http://arxiv.org/abs/0709.1667 ER -