  The paper studies the emergence and stability of cooperative behavior in
populations of agents who interact among themselves in Prisoner's Dilemma games
and who are allowed to choose their partners. The population is then subject to
evolutionary pressures, based on individual payoffs from multiple encounters. A
simple formula for signaling and recognition is introduced, which allows the
agents to guess prospective partner strategy and to refuse the game if the
predicted outcome is unfavorable. We present both algebraic formulation of the
average payoffs and results of computer simulations of evolution of such
society. The simulations result in surprising variety of behavior. We discuss
possible interpretations of the results as well as relationship between
artificial `computer time' and real time of possible social and biological
systems that the model might be applied to.
