Parrondo effect: Exploring the nature-inspired framework on periodic functions

Recently, a population model has been analyzed using the framework of Parrondo's paradox to explain how behavior-switching organisms can achieve long-term survival, despite each behavior individually resulting in extinction. By incorporating environmental noise, the model has been shown to be robust to natural variations. Apart from the role of noise, the apparent ubiquity of quasi-periodicity in nature also motivates a more comprehensive understanding of periodically-coupled models of Parrondo's paradox. Such models can enable a wider range of applications of the Parrondo effect to biological and social systems. In this paper, we modify the canonical Parrondo's games to show how the Parrondo effect can still be achieved despite the increased complexity in periodically-noisy environments. Our results suggest the extension of Parrondo's paradox to real-world phenomena strongly subjected to periodic variations, such as ecological systems experiencing seasonal changes, disease in wildlife and humans, or resource management.