Miras Karine, Ferrante Eliseo, Eiben A E
Computer Science Department, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Autonomous Robotics Research Centre, Technology Innovation Institute, Abu Dhabi, United Arab Emirates.
Front Robot AI. 2020 Oct 1;7:107. doi: 10.3389/frobt.2020.00107. eCollection 2020.
Evolutionary robot systems are usually affected by the properties of the environment indirectly through selection. In this paper, we present and investigate a system where the environment also has a direct effect-through regulation. We propose a novel robot encoding method where a genotype encodes multiple possible phenotypes, and the incarnation of a robot depends on the environmental conditions taking place in a determined moment of its life. This means that the morphology, controller, and behavior of a robot can change according to the environment. Importantly, this process of development can happen at any moment of a robot's lifetime, according to its experienced environmental stimuli. We provide an empirical proof-of-concept, and the analysis of the experimental results shows that environmental regulation improves adaptation (task performance) while leading to different evolved morphologies, controllers, and behavior.
进化机器人系统通常通过选择间接受到环境特性的影响。在本文中,我们展示并研究了一种系统,其中环境还通过调节产生直接影响。我们提出了一种新颖的机器人编码方法,其中一个基因型编码多种可能的表型,并且机器人的化身取决于其生命中特定时刻所发生的环境条件。这意味着机器人的形态、控制器和行为可以根据环境而变化。重要的是,这种发育过程可以根据机器人所经历的环境刺激在其生命周期的任何时刻发生。我们提供了一个实证概念验证,对实验结果的分析表明,环境调节在导致不同的进化形态、控制器和行为的同时提高了适应性(任务性能)。