In the blockchain network, to get rewards in blockchain, participants pay for various forms of competition such as computing power, stakes, and other resources. Because need a certain cost, individual cooperate maintain long-term stability jointly. course competition, game between each has appeared invisibly. To better understand design cooperation mechanisms, this paper, we constructed framewo...

We study a class of population games called stable games. These games are characterized by self-defeating externalities: when agents revise their strategies, the improvements in the payoffs of strategies to which revising agents are switching are always exceeded by the improvements in the payoffs of strategies which revising agents are abandoning. We prove that the set of Nash equilibria of a s...

Evolutionary dynamics are affected by population structure, mutation rates and update rules. Spatial or network structure facilitates the clustering of strategies, which represents a mechanism for the evolution of cooperation. Mutation dilutes this effect. Here we analyze how mutation influences evolutionary clustering on graphs. We introduce new mathematical methods to evolutionary game theory...

Researchers have been applying artificial/computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioA...

Evolutionary game dynamics is the application of population dynamical methods to game theory. It has been introduced by evolutionary biologists, anticipated in part by classical game theorists. In this survey, we present an overview of the many brands of deterministic dynamical systems motivated by evolutionary game theory, including ordinary differential equations (and, in particular, the repl...

The main purpose of this paper is to solve an inverse random differential equation problem using evolutionary algorithms. Particle Swarm Algorithm and Genetic Algorithm are two algorithms that are used in this paper. In this paper, we solve the inverse problem by solving the inverse random differential equation using Crank-Nicholson's method. Then, using the particle swarm optimization algorith...

We study the effects of conformist transmission on the evolutionary dynamics of the Prisoner’s Dilemma, the Snowdrift and the Stag Hunt games in both well-mixed and spatially structured populations. The addition of conformism introduces a transformation of the payoff matrix that favours the stability of pure equilibria and reduces the basin of attraction of risk dominant equilibria. When both c...