Learning strategies for optimised fitness in a model of cyclic dominance
Year: 2025
Type: article
Abstract: A major problem in evolutionary biology is how species learn and adapt under the constraints of environmental conditions and the competition of other species. Models of cyclic dominance provide simplified settings in which such questions can be addressed using methods from theoretical physics. We investigate how a privileged (‘smart’) species optimises its population by adopting advantageous strategies in one such model. We use a reinforcement learning algorithm, which successfully identifies optimal strategies based on a survival-of-the-weakest effect, including directional incentives to avoid predators. We also characterise the steady-state behaviour of the system in the presence of the smart species and compare it with the symmetric case where all species are equivalent.
Source: New Journal of Physics
Authors: Honghao Yu, Robert L Jack
Institution: University of Cambridge
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,610
OpenAlex ID: W4413318071