Reinforcement learning of biomimetic navigation: a model problem for sperm chemotaxis.

Autor: Mohamed O; Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Pok Fu Lam, Hong Kong, China., Tsang ACH; Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Pok Fu Lam, Hong Kong, China. alancht@hku.hk.
Jazyk: angličtina
Zdroj: The European physical journal. E, Soft matter [Eur Phys J E Soft Matter] 2024 Sep 27; Vol. 47 (9), pp. 59. Date of Electronic Publication: 2024 Sep 27.
DOI: 10.1140/epje/s10189-024-00451-6
Abstrakt: Motile biological cells can respond to local environmental cues and exhibit various navigation strategies to search for specific targets. These navigation strategies usually involve tuning of key biophysical parameters of the cells, such that the cells can modulate their trajectories to move in response to the detected signals. Here we introduce a reinforcement learning approach to modulate key biophysical parameters and realize navigation strategies reminiscent to those developed by biological cells. We present this approach using sperm chemotaxis toward an egg as a paradigm. By modulating the trajectory curvature of a sperm cell model, the navigation strategies informed by reinforcement learning are capable to resemble sperm chemotaxis observed in experiments. This approach provides an alternative method to capture biologically relevant navigation strategies, which may inform the necessary parameter modulations required for obtaining specific navigation strategies and guide the design of biomimetic micro-robotics.
(© 2024. The Author(s).)
Databáze: MEDLINE
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