  Evolutionary spatial 2 x 2 games between heterogeneous agents are analyzed
using different variants of cellular automata (CA). Agents play repeatedly
against their nearest neighbors 2 x 2 games specified by a rescaled payoff
matrix with two parameteres. Each agent is governed by a binary Markovian
strategy (BMS) specified by 4 conditional probabilities [p_R, p_S, p_T, p_P]
that take values 0 or 1. The initial configuration consists in a random
assignment of "strategists" among the 2^4= 16 possible BMS. The system then
evolves within strategy space according to the simple standard rule: each agent
copies the strategy of the neighbor who got the highest payoff. Besides on the
payoff matrix, the dominant strategy -and the degree of cooperation- depend on
i) the type of the neighborhood (von Neumann or Moore); ii) the way the
cooperation state is actualized (deterministically or stochastichally); and
iii) the amount of noise measured by a parameter epsilon. However a robust
winner strategy is [1,0,1,1].
