In this study, we investigate the underlying population dynamics when a group of agents compete for a finite, non-stationary resource. Based on a hybridized binary choice resource allocation game, at each time step individual agents make a decision whether to access the resource based on their own adaptive strategy and the aggregate history of previous resource utilization data. Agents, who are able to correctly identify the balance between supply and demand at the current time-step, are rewarded. However, agents who make an incorrect decision are penalized. Extensive numerical simulations show that the transient and long-run aggregate properties of the systems are dependent upon the rate of change of the resource availability as well as the heterogeneous decision making strategies adopted by the agent population.