竞争协同进化中的求新
Novelty Search in Competitive Coevolution
摘要：
使用竞争性共同进化系统的主要动机之一是它们能够利用竞争物种之间的军备竞赛来进化出越来越复杂的解决方案。然而，这种军备竞赛可能难以持续，而且已经表明，相互竞争的物种往往过早地趋同于某些行为类别。在本文中，我们调查新颖性搜索，行为新颖性驱动的进化技术，可以克服收敛的共同进化。我们提出了三种方法应用新颖性搜索两个物种的共同进化系统：（一）得分两个人口根据行为的新颖性;（二）得分一个人口根据新颖性，和其他根据健身;和（iii）得分两个人口的新颖性和健身的组合。我们评估的方法在捕食者-猎物的追求任务。我们的研究结果表明，基于新颖性的方法可以发展出一个显着更多样化的解决方案，相比传统的健身为基础的协同进化。
英文摘要：
One of the main motivations for the use of competitive coevolution systems is their ability to capitalise on arms races between competing species to evolve increasingly sophisticated solutions. Such arms races can, however, be hard to sustain, and it has been shown that the competing species often converge prematurely to certain classes of behaviours. In this paper, we investigate if and how novelty search, an evolutionary technique driven by behavioural novelty, can overcome convergence in coevolution. We propose three methods for applying novelty search to coevolutionary systems with two species: (i) score both populations according to behavioural novelty; (ii) score one population according to novelty, and the other according to fitness; and (iii) score both populations with a combination of novelty and fitness. We evaluate the methods in a predator-prey pursuit task. Our results show that novelty-based approaches can evolve a significantly more diverse set of solutions, when compared to traditional fitness-based coevolution.
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