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Robots as models of evolving systems.

Gao WangTrung V PhanShengkai LiJing WangYan PengGuo ChenJunle QuDaniel I GoldmanSimon Asher LevinKenneth J PientaSarah R AmendRobert H AustinLiyu Liu
Published in: Proceedings of the National Academy of Sciences of the United States of America (2022)
Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, and breeding. We map the quasi-steady-state surviving local density of the robots onto a multidimensional abstract “survival landscape.” We show that robot death in complex, self-adaptive stress landscapes proceeds by a general lowering of the robotic genetic diversity, and that stochastically changing landscapes are the most difficult to survive.
Keyphrases
  • genetic diversity
  • intellectual disability
  • robot assisted
  • free survival