  In a co-evolutionary context, the survive probability of individual elements
of a system depends on their relation with their neighbors. The natural
selection process depends on the whole population, which is determined by local
events between individuals. Particular characteristics assigned to each
individual, as larger memory, usually improve the individual fitness, but an
agent possess also endogenous characteristics that induce to re-evaluate her
fitness landscape and choose the best-suited kind of interaction, inducing a
non absolute value of the outcomes of the interaction. In this work, a novel
model with agents combining memory and rational choice is introduced, where
individual choices in a complex fitness landscape induce changes in the
distribution of the number of agents as a function of the time. In particular,
the tail of this distribution is fat compared with distributions for agents
interacting only with memory.
