Statistical fluctuations in population bargaining in the ultimatum game: static and evolutionary aspects.

We explore the emergent behavior in heterogeneous populations where players negotiate via an ultimatum game: two players are offered a gift, one of them (the proposer) suggests how to divide the offer while the other player (the responder) can either accept or reject the deal. Rejection is detrimental to both players as it results in no earnings. In this context, our contribution is twofold: (i) we consider a population where the distribution of used strategies is constant over time and properties of the random payoff received by the players (average and higher moments) are reported from simple exact methods and corroborated by computer simulations; (ii) the evolution of a population is analyzed via Monte Carlo simulations where agents may change independently the proposing and accepting parameters of their strategy depending on received payoffs. Our results show that evolution leads to a stationary state in which wealth (accumulated payoff) is fairly distributed. As time evolves, an increase in average payoff and a simultaneous variance decrease is observed when we use a dynamics based on a probabilistic version of the saying: "One should not comply with small earnings, but one's greed must be limited."