Environment-driven distributed evolutionary adaptation in a population of autonomous robotic agents
Environment-driven distributed evolutionary adaptation in a population of autonomous robotic agents
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DOI：
10.1080/13873954.2011.601425
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发表时间：
2012-01-01
影响因子：
1.9
通讯作者：
Winfield, Alan F. T.
中科院分区：
文献类型：
--
作者：
Bredeche, Nicolas;Montanier, Jean-Marc;Winfield, Alan F. T.
这篇文章关注的是一个固定大小的人口的自主代理人面临未知的，可能不断变化的环境。其动机是设计一个具体的进化算法，可以科普隐式的适应度函数隐藏在环境中，以便提供适应在长期的人口水平。所提出的算法，称为MEDEA，被证明是有效的，在未知的环境和鲁棒性的突然和不可预测的环境变化。研究了对特定行为策略达成共识的情况，特别关注算法稳定性。最后，一个真实世界的实现算法描述了人口的20个真实世界的电子冰球机器人。
This article is concerned with a fixed-size population of autonomous agents facing unknown, possibly changing, environments. The motivation is to design an embodied evolutionary algorithm that can cope with the implicit fitness function hidden in the environment so as to provide adaptation in the long run at the level of population. The proposed algorithm, termed MEDEA, is shown to be both efficient in unknown environments and robust to abrupt and unpredicted changes in the environment. The emergence of consensus towards specific behavioural strategies is examined, with a particular focus on algorithmic stability. Finally, a real-world implementation of the algorithm is described with a population of 20 real-world e-puck robots.