  We study the dynamics of the "Kolkata Paise Restaurant problem". The problem
is the following: In each period, N agents have to choose between N
restaurants. Agents have a common ranking of the restaurants. Restaurants can
only serve one customer. When more than one customer arrives at the same
restaurant, one customer is chosen at random and is served; the others do not
get the service. We first introduce the one-shot versions of the Kolkata Paise
Restaurant problem which we call one-shot KPR games. We then study the dynamics
of the Kolkata Paise Restaurant problem (which is a repeated game version of
any given one shot KPR game) for large N. For statistical analysis, we explore
the long time steady state behavior. In many such models with myopic agents we
get under-utilization of resources, that is, we get a lower aggregate payoff
compared to the social optimum. We study a number of myopic strategies,
focusing on the average occupation fraction of restaurants.
