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Morphological Attractors in Darwinian and Lamarckian Evolutionary Robot Systems

机译:达尔文和拉马克进化机器人系统中的形态吸引子

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Morphological evolution in a robotic system produces novel robot bodies after each reproduction event. This implies the necessity for life-time learning so that newborn robots can acquire a controller that fits their body. Thus, we obtain a system where evolution and learning are combined. This combination can be Darwinian or Lamarckian and in this paper, we compare the two. In particular, we investigate the evolved morphologies under these regimes for modular robots evolved for good locomotion. Using eight quantifiable morphological descriptors to characterize the physical properties of robots we compare the regions of attraction in the resulting 8-dimensional space. The results show prominent differences in symmetry, size, proportion, and coverage.
机译:机器人系统中的形态演变在每次再现事件后产生新颖的机器人体。这意味着终身学习的必要性,以便新生机器人可以获得适合身体的控制器。因此,我们获得了一个改进和学习的系统。这种组合可以是达尔文或拉马克,在本文中,我们比较这两者。特别是,我们调查在这些制度下的演进形态,以便模块化机器人进化为良好的运动。使用八个可量化的形态描述符来表征机器人的物理性质,我们比较所产生的8维空间的吸引区域。结果表明对称性,大小,比例和覆盖范围的突出差异。

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