Prisoner's dilemma on a network of heterogenous agents: cooperation and learning co-evolution

LUIS G. MOYANO; ANGEL SANCHEZ

Pamplona

Taller; Net-Works 2008; 2008

U. Rey Juan Carlos

In the Prisoner's Dilemma game, agents play with each other and update their strategies in every generation according to some microscopic dynamical rule. In this work, we explore the Prisoner's Dilemma on heterogeneous networks, comprising two kinds of agents, with different update rules. We investigate two setups: in the first one, agents' update rules remain fixed for the entire evolution of the system; in the second one, agents update both strategy and update rule in every generation. Our results show that, for an important range of parameters of the game, the final state of the system is very different from the one obtained with homogeneous agents with a fixed update rule. We study representative dynamical rules and show that certain types become extinct while others prevail. We describe the new and rich variety of final outcomes that arise from the co-evolutionary process.