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Morphological Attractors in Darwinian and Lamarckian Evolutionary Robot Systems

Milan Jelisavcic, Karine Miras, A. E. Eiben

发表年份
2018
引用次数
7

摘要

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.

关键词

RobotEvolutionary roboticsArtificial intelligenceDarwinismModular designComputer scienceSelf-reconfiguring modular robotController (irrigation)Evolutionary computationMobile robot

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