A Minimal Developmental Model Can Increase Evolvability in Soft Robots
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Abstract (arXiv)
Different subsystems of organisms adapt over many time scales, such as rapid changes in the nervous system (learning), slower morphological and neurological change over the lifetime of the organism (postnatal development), and change over many generations (evolution). Much work has focused on instantiating learning or evolution in robots, but relatively little on development. Although many theories have been forwarded as to how development can aid evolution, it is difficult to isolate each such proposed mechanism. Thus, here we introduce a minimal yet embodied model of development: the body of the robot changes over its lifetime, yet growth is not influenced by the environment. We show that even this simple developmental model confers evolvability because it allows evolution to sweep over a larger range of body plans than an equivalent non-developmental system, and subsequent heterochronic mutations 'lock in' this body plan in more morphologically-static descendants. Future work will involve gradually complexifying the developmental model to determine when and how such added complexity increases evolvability.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Jun 2017.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 1.
5 papers.
- 2022HyperNCA: Growing Developmental Networks with Neural Cellular Automatacited by 18
- 2023Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programscited by 17
- 2023Design Optimizer for Planar Soft-Growing Robot Manipulatorscited by 2
- 2022Morphological Wobbling Can Help Robots Learncited by 1
- 2024Design Optimizer for Soft Growing Robot Manipulators in Three-Dimensional Environmentscited by 0
- 2024Design Optimizer for Soft Growing Robot Manipulators in Three-Dimensional Environments31 Dec 2024
- 2023Design Optimizer for Planar Soft-Growing Robot Manipulators5 Oct 2023
- 2023Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs17 Jul 2023
- 2022Morphological Wobbling Can Help Robots Learn5 May 2022
- 2022HyperNCA: Growing Developmental Networks with Neural Cellular Automata25 Apr 2022