Evolutionary games are used in various elds stretching from economics to biology. Most assume a constant payoff matrix, although some works also consider dynamic payoff matrices. In this article we propose a possibility of switching the system between two regimes with different sets of payoff matrices. Such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A nite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution by applying the Hamilton-Jacobi formalism. Therefore, we present an exactly solvable version of an evolutionary game with annealed noise in the payoff matrix.
Lethal mutations are very common in asexual evolution, both in RNA viruses and in the clonal evolution of cancer cells. In a special case of lethal mutations (truncated selection), after a critical total number of mutations the replicator (the virus or the cell) has no offspring. We consider the Eigen and Crow–Kimura models with truncated fitness landscapes, and calculate the fraction of viable replicators (that do have offspring) in the population. We derive a formula for the fraction of the population with nonlethal replicators for the case of a uniform distribution of lethal sequences in the sequence space. We assume that our results can be applied to the origin of life and cancer biology.