Track genomics, neuroscience and molecular biology.
Search papers, labs, and topics across Lattice.
We analyze stochastic evolutionary dynamics in finite, structured populations using a birth-death framework on random regular networks, extending evolutionary game theory to multi-strategy scenarios. By identifying critical degree thresholds, we demonstrate that network structure significantly governs evolutionary stability and invasion dynamics, moving beyond infinite-population assumptions. The key result is that the interplay of initial mutant composition, population structure, and stochasticity dictates the evolutionary trajectory of resident populations.
Network degree, not just strategy payoff, dictates evolutionary stability in finite, multi-strategy populations.
Stochasticity shapes evolutionary dynamics in finite populations beyond the reach of infinite-population theories. Using a stochastic birth--death framework on random regular networks, we establish evolutionary stability criteria for finite structured populations playing three-strategy games and identify critical degree thresholds governing invasion dynamics. Our framework goes beyond two-strategy evolutionary games to reveal that the initial composition of multi-type mutants, together with population structure and stochasticity, shapes the evolutionary fate of the resident population.