In the most extensive robot evolution systems, both the bodies and the brains of the robots undergo evolution and the brains of 'infant' robots are also optimized by a learning process immediately after 'birth'. This paper is concerned with the brain evolution mechanism in such a system. In particular, we compare four options obtained by combining asexual or sexual brain reproduction with Darwinian or Lamarckian evolution mechanisms. We conduct experiments in simulation with a system of evolvable modular robots on two different tasks. The results show that sexual reproduction of the robots' brains is preferable in the Darwinian framework, but the effect is the opposite in the Lamarckian system (both using the same infant learning method). Our experiments suggest that the overall best option is asexual reproduction combined with the Lamarckian framework, as it obtains better robots in terms of fitness than the other three. Considering the evolved morphologies, the different brain reproduction methods do not lead to differences. This result indicates that the morphology of the robot is mainly determined by the task and the environment, not by the brain reproduction methods.
翻译:在最广泛的机器人进化系统中,机器人的身体和大脑都经历了进化;而'婴儿'机器人的大脑也得到了优化,并在'出生'后立即进行学习过程。本文关注这种系统中的大脑进化机制。特别是,我们比较了四种选项,这四种选项是通过组合性脑繁殖法和达尔文或拉马克进化机制实现的。我们在可演化模块化机器人系统中的两个不同任务上进行了模拟实验。结果表明,在达尔文框架下,机器人大脑的性繁殖是最佳选择,但在拉马克体系中效果相反(都使用相同的婴儿学习方法)。我们的实验表明,总体最佳选项是通过使用拉马克机制的无性繁殖,因为它在适应度方面比其他三个方法都更好。考虑到进化后的形态,不同的大脑繁殖方法并不导致差异。这个结果表明,机器人的形态主要是由任务和环境来决定的,而不是由大脑的繁殖方法来决定的。