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Updated: Mar 21, 2026

New Variations for Strategy Set-shifting in the Rat
Published on: January 23, 2017
Parrondo-like evolutionary advantage from stochastic switching between specialist and generalist strategies in
De-Ming Liu1, Zhi-Xi Wu1, Jian-Yue Guan1
1Lanzhou University, Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, Key Laboratory of Quantum Theory and Applications of MoE, Gansu Provincial Research Center for Basic Disciplines of Quantum Physics, and Institute of Computational Physics and Complex Systems, Lanzhou 730000, China.
Abstract:
Organisms have evolved various mechanisms to cope with stochastic environmental fluctuations, and the survival strategies of being generalists and specialists are particularly crucial in this context. Generalists prioritize long-term population survival, providing equal benefits in both favorable and unfavorable environments. In contrast, specialists focus on short-term rapid growth, with benefits that differ significantly in different environmental conditions. In this paper we investigate the invading process of mutants in a finite wild-type population under fluctuating environmental conditions, aiming to elucidate the potential survival strategies that mutants can adopt to maximize their fixation probability. To this end, we construct and analyze a dynamic model in which the population dynamics is governed by a birth-death process, and the fluctuating environment is modeled by a Markov chain. We explore scenarios in which the mutant population adopts alternating strategies between specialist and generalist according to either responsive or stochastic switching schemes. Interestingly, we find that mutant populations adopting stochastic switching strategies achieve higher fixation probabilities than those using just pure strategies. This counterintuitive result is reminiscent of Parrondo's paradox in complex systems, where an unexpected victory arises from two individually losing strategies, provided that they are utilized in a particular or random manner. Our work reveals that in stochastic environments, survival in the evolutionary process depends not on the superiority of a specific strategy but on the population's adaptability.
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