用于有效分布式算法发现的无信任并行局部搜索
Trustless parallel local search for effective distributed algorithm discovery
摘要：
元启发式搜索策略已经证明了它们在各种情况下对人造解决方案的有效性。它们通常在局部搜索区域开发中是有效的，并且它们的整体性能在很大程度上受到探索和开发之间的平衡的影响。并行局部搜索的最新发展探索了利用高效的局部搜索并达到令人印象深刻的结果的方法。然而，这限制了私有可信计算机集群内的节点的扩展潜力。在这项研究中，我们提出了一种新的区块链协议，允许并行本地搜索扩展到不可信和匿名的计算节点。该协议引入了可公开验证的性能评估的局部最优值报告的每个节点，创造了一个竞争的环境之间的局部搜索。这是加强与经济刺激，以产生良好的解决方案，提供协调之间的节点，因为每个节点试图探索不同部分的搜索空间击败他们的竞争。
英文摘要：
Metaheuristic search strategies have proven their effectiveness against man-made solutions in various contexts. They are generally effective in local search area exploitation, and their overall performance is largely impacted by the balance between exploration and exploitation. Recent developments in parallel local search explore methods to take advantage of the efficient local exploitation of searches and reach impressive results. This however restricts the scaling potential to nodes within a private, trusted computer cluster. In this research we propose a novel blockchain protocol that allows parallel local search to scale to untrusted and anonymous computational nodes. The protocol introduces publicly verifiable performance evaluation of the local optima reported by each node, creating a competitive environment between the local searches. That is strengthened with economical stimuli for producing good solutions, that provide coordination between the nodes, as every node tries to explore different sections of the search space to beat their competition.
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