论文标题
无信任的平行本地搜索有效分布式算法发现
Trustless parallel local search for effective distributed algorithm discovery
论文作者
论文摘要
在各种情况下，元神经搜索策略证明了它们对人造解决方案的有效性。它们通常在当地搜索区域开发中有效，并且它们的整体绩效在很大程度上受到勘探和剥削之间的平衡影响。 并行本地搜索的最新发展探讨了利用有效的本地搜索搜索并取得令人印象深刻的结果的方法。但是，这将缩放潜力限制在一个私人，值得信赖的计算机群集中的节点。 在这项研究中，我们提出了一种新型的区块链协议，该协议允许并行局部搜索扩展到不受信任和匿名的计算节点。该协议介绍了每个节点报告的本地优点的公开验证性能评估，从而在本地搜索之间创造了竞争性环境。由于每个节点试图探索搜索空间的不同部分以击败他们的竞争，因此可以通过经济刺激来加强良好的解决方案。
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.
