Deep learning approach for predicting the replicator equation in evolutionary game theory

This paper presents a physics-informed deep learning approach for predicting the replicator equation, allowing accurate forecasting of population dynamics. This methodological innovation allows us to derive governing differential or difference equations for systems that lack explicit mathematical models. We used the SINDy model first introduced by Fasel, Kaiser, Kutz, Brunton, and Brunt 2016a to get the replicator equation, which will significantly advance our understanding of evolutionary biology, economic systems, and social dynamics. NTRODUCTION Game theory helps to understand how strategic behaviours evolve and persist in biological, social, and economic systems where individuals interact. It also helps in how complex social behaviours and strategies can evolve and persist in diverse contexts.