One of the interesting extensions of evolutionary game theory is to limit the possible interactions of each agent to only the subset of population, mainly to those agents that belong to the spatial or social neighborhood of the particular individual. In our article we thus extend the existing literature on evolutionary games on networks by examining how both the network topologies and the mechanisms, in our case imitation strategies, through which particular behavior spreads in the population affect the evolutionary dynamics of the game.
Our agent-based computational experiments show that both the interaction structure and the way how agents choose to imitate the others strongly influence the dynamics of the game. We thus provide both new insights in the study of the evolutionary games on networks and test of the robustness of previously obtained results.

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