An Information-Based Neural Approach to Constraint Satisfaction

Details An Information-Based Neural Approach to Constraint Satisfaction An Information-Based Neural Approach to Constraint Satisfaction

2001-05-16

arxiv.org/abs/cond-mat/0105319v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

13 pages, 3 figures,(to appear in Neural Computation)

Scientific paper

A novel artificial neural network approach to constraint satisfaction problems is presented. Based on information-theoretical considerations, it differs from a conventional mean-field approach in the form of the resulting free energy. The method, implemented as an annealing algorithm, is numerically explored on a testbed of K-SAT problems. The performance shows a dramatic improvement to that of a conventional mean-field approach, and is comparable to that of a state-of-the-art dedicated heuristic (Gsat+Walk). The real strength of the method, however, lies in its generality -- with minor modifications it is applicable to arbitrary types of discrete constraint satisfaction problems.

Affiliated with

Also associated with

No associations

Rating

An Information-Based Neural Approach to Constraint Satisfaction does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with An Information-Based Neural Approach to Constraint Satisfaction, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and An Information-Based Neural Approach to Constraint Satisfaction will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-151288