gets the payoff given by the table when playing again the strategies in the columns.[]{data-label="tabla2"}

In order to study the possibility that the players can change their strategies as a result of their previous interactions, thus generating an evolutionary dynamics of strategies, many authors started to work with the iterated Prisoner Dilemma, in which players interact by iteratively playing the game several times. The history of successes or failures of each player is recorded in what is called his cumulative payoff. How the players use the information accumulated in their own and others cumulative payoffs is what defines the rules of evolution. Operationally, the evolutionary dynamics acts at a certain instance of the game, for example after everybody has played against everybody else, when players decide whether to change strategies or not, following certain update rules. Before all the players start again playing the game, all the cumulative payoffs are set to $0$. The spectra of rules of evolution is wide and ranges from purely deterministic to stochastic dynamics [@oht; @sza; @now2; @moy; @hau].

Complementary to the evolutionary aspects mentioned above, many authors started to analyze spatial games in order to cope with the limitations associated with the assumption that 