Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment
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. W...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2016-12-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/2812.pdf |
| _version_ | 1827606439357579264 |
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| author | Yao Yao Veronique Storme Kathleen Marchal Yves Van de Peer |
| author_facet | Yao Yao Veronique Storme Kathleen Marchal Yves Van de Peer |
| author_sort | Yao Yao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T06:38:18Z |
| format | Article |
| id | doaj.art-82158c9db91344159cb289ccab4470e0 |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T06:38:18Z |
| publishDate | 2016-12-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-82158c9db91344159cb289ccab4470e02023-12-03T10:55:04ZengPeerJ Inc.PeerJ2167-83592016-12-014e281210.7717/peerj.2812Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environmentYao Yao0Veronique Storme1Kathleen Marchal2Yves Van de Peer3Department of Plant Systems Biology, VIB, Ghent, BelgiumDepartment of Plant Systems Biology, VIB, Ghent, BelgiumDepartment of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, BelgiumDepartment of Plant Systems Biology, VIB, Ghent, BelgiumWe 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.https://peerj.com/articles/2812.pdfComplex adaptationComplex adaptive systemsSelf-organizing systemsArtificial lifeSwarm robotsEmergent behaviour |
| spellingShingle | Yao Yao Veronique Storme Kathleen Marchal Yves Van de Peer Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment PeerJ Complex adaptation Complex adaptive systems Self-organizing systems Artificial life Swarm robots Emergent behaviour |
| title | Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment |
| title_full | Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment |
| title_fullStr | Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment |
| title_full_unstemmed | Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment |
| title_short | Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment |
| title_sort | emergent adaptive behaviour of grn controlled simulated robots in a changing environment |
| topic | Complex adaptation Complex adaptive systems Self-organizing systems Artificial life Swarm robots Emergent behaviour |
| url | https://peerj.com/articles/2812.pdf |
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