  We propose and study an evolutionary minority game (EMG) in which the agents
are allowed to choose among three possible options. Unlike the original EMG
where the agents either win or lose one unit of wealth, the present model
assigns one unit of wealth to the winners in the least popular option, deducts
one unit from the losers in the most popular option, and awards $R$ ($-1<R< 1$)
units for those in the third option. Decisions are made based on the
information in the most recent outcomes and on the characteristic probabilities
of an agent to follow the predictions based on recent outcomes. Depending on
$R$, the population shows a transition from self-segregation in difficult
situations ($R<R_{c}$) in which the agents tend to follow extreme action to
cautious or less decisive action for $R>R_{c}$, where $R_{c}(N)$ is a critical
value for optimal performance of the system that drops to zero as the number of
agents $N$ increases.
