A Stochastic Hyperheuristic for Unsupervised Matching of Partial Information

Kieran R. C. Greer
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引用次数: 3

Abstract

This paper (Revised version of a white paper "Unsupervised Problem-Solving by Optimising through Comparisons," originally published on DCS and Scribd, October 2011.) describes the implementation and functionality of a centralised problem solving system that is included as part of the distributed "licas" system. This is an open source framework for building service-based networks, similar to what you would do on a Cloud or SOA platform. While the framework can include autonomous and distributed behaviour, the problem-solving part can performmore complex centralised optimisation operations and then feed the results back into the network. The problem-solving system is based on a novel type of evaluationmechanism that prefers comparisons between solution results, over maximisation. This paper describes the advantages of that and gives some examples of where it might perform better, including possibilities related to a more cognitive system.
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部分信息无监督匹配的随机超启发式算法
本文(“通过比较优化解决无监督问题”白皮书的修订版,最初发表于DCS和Scribd, 2011年10月)描述了作为分布式“许可证”系统一部分的集中式问题解决系统的实现和功能。这是一个用于构建基于服务的网络的开源框架,类似于您在云或SOA平台上所做的工作。虽然框架可以包含自治和分布式行为,但解决问题的部分可以执行更复杂的集中优化操作,然后将结果反馈给网络。解决问题的系统是基于一种新型的评估机制,更喜欢解决方案结果之间的比较,而不是最大化。本文描述了这种方法的优点,并给出了一些可能表现更好的例子,包括与认知系统相关的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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