The use of a data envelopment analysis efficient rule to produce a steady and high cooperation frequency in a spatial evolvement game

We use the data envelopment analysis (DEA) method to estimate the relative efficiency of the current strategy for each player in a game by taking the spatial distribution of strategies as input and the total payoff as output. Based on the optimal value of the DEA model, we present a DEA efficient rule to update the strategy in evolutionary games. Simulations of the prisoner’s dilemma game (PDG) [4] and the snowdrift game (SG) on two-dimensional regular lattices of four, six, and eight neighbors with periodic boundary conditions, are carried out; the results show the emergence of high and stable cooperator frequency. The heuristic analysis of the DEA efficient rule are discussed in detail. Our work may be helpful in exploring the promotion of cooperator behavior.