An evolutionary game optimization to vertex cover of dynamic networks

Vertex cover is one of the best known combinatorial optimization problems. Treating each vertex as an intelligent rational agent, we model vertex cover problem under the framework of evolutionary game theory, where players have different rates of forming and breaking links, and such linking dynamics introduces a transformation of the payoff matrix. We propose an algorithm to solve the vertex cover problem of dynamic networks, and find that a better approximate solution to the minimum vertex cover of dynamic networks can be obtained by choosing proper parameters.