摘要翻译：
本文研究了细胞遗传算法中的探索/开发权衡问题。我们定义了一个新的选择方案，中心选择，它是可调谐的，允许用单一参数控制选择压力。利用平衡模型研究了中心选择对选择压力的影响，提出了一种新的考虑问题相关统计量和选择压力的勘探/开采权衡模型：间断平衡模型。二次指派问题和NK-景观的表现证明了这两类问题的最优勘探/开发权衡。用间断平衡模型解释了这些结果。
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英文标题：
《Centric selection: a way to tune the exploration/exploitation trade-off》
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作者：
David Simoncini, S\'ebastien Verel, Philippe Collard, Manuel Clergue
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  In this paper, we study the exploration / exploitation trade-off in cellular genetic algorithms. We define a new selection scheme, the centric selection, which is tunable and allows controlling the selective pressure with a single parameter. The equilibrium model is used to study the influence of the centric selection on the selective pressure and a new model which takes into account problem dependent statistics and selective pressure in order to deal with the exploration / exploitation trade-off is proposed: the punctuated equilibria model. Performances on the quadratic assignment problem and NK-Landscapes put in evidence an optimal exploration / exploitation trade-off on both of the classes of problems. The punctuated equilibria model is used to explain these results.
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PDF链接：
https://arxiv.org/pdf/1107.4163