An optimal algorithm to compute maximal relaxations in parallel

Mingyue Wang, Na Wang, Chi Zhang, Dehong Ma, Zhanshan Li
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Abstract

The study of constraint satisfaction problems touches many aspects of artificial intelligence. It is the premise of dominant interactive constraint satisfaction algorithms that users' preference has complete order. To accord more with practical situation, Haijiao Shen [3] did some research on the situation in which users' preferences have partial order and put forward the related algorithm in 2011. By introducing a constraint set M to decrease the spread of redundancy, we optimize her algorithm. We also prove the validity of our new algorithm and test it on some benchmarks. It is indicated by test result that the optimized algorithm MulExp can save up to 18% of examine times and up to 12% of solving time, which greatly increases the efficiency of solving process.
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并行计算最大松弛量的最优算法
约束满足问题的研究涉及人工智能的许多方面。主导交互约束满足算法的前提是用户偏好具有完全有序性。为了更符合实际情况,沈海蛟[3]在2011年对用户偏好偏序的情况进行了研究,并提出了相关算法。通过引入约束集M来减少冗余的扩散,对该算法进行了优化。我们还证明了新算法的有效性,并在一些基准测试中进行了测试。实验结果表明,优化后的mullexp算法最多可节省18%的检测次数和12%的求解时间,大大提高了求解过程的效率。
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