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：在最为广泛的机器人进化系统中，机器人的身体和大脑均经历进化过程，且"新生"机器人的大脑在"诞生"后立即通过学习过程进行优化。本文关注此类系统中的大脑进化机制，具体比较了将无性或有性大脑繁殖与达尔文或拉马克进化机制组合而成的四种方案。我们在可进化模块化机器人系统的仿真中对两种不同任务进行了实验。结果表明，在达尔文框架下机器人大脑的有性繁殖更优，但在拉马克框架下效果相反（两者采用相同的幼体学习方法）。我们的实验表明，整体最优方案是将无性繁殖与拉马克框架相结合，该方法在适应度方面能获得优于其他三种方案的机器人。考虑到进化后的形态，不同的大脑繁殖方法并未导致差异。这一结果表明，机器人的形态主要由任务和环境决定，而非大脑繁殖方法。