most citedUnweighted Stochastic Local Search can be Effective for Random CSP Benchmarks

11 citations · 11 across the 1 of their papers we have counts for

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1 paper

cs.AI2014★ 11 cited

Unweighted Stochastic Local Search can be Effective for Random CSP Benchmarks

Christopher D. Rosin

We present ULSA, a novel stochastic local search algorithm for random binary constraint satisfaction problems (CSP). ULSA is many times faster than the prior state of the art on a…