Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

PeerJ

article

Yao Yao¹  Veronique Storme¹  Kathleen Marchal²  Yves Van de Peer¹ 

[1] Department of Plant Systems Biology;Department of Plant Biotechnology and Bioinformatics, Ghent University;Bioinformatics Institute Ghent;Department of Information Technology, iMinds, Ghent University;Department of Genetics, Genomics Research Institute, University of Pretoria

关键词: Complex adaptation;    Complex adaptive systems;    Self-organizing systems;    Artificial life;    Swarm robots;    Emergent behaviour;   

DOI  :  10.7717/peerj.2812

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population.

【 授权许可】

CC BY