Retirement savings decisions can be influenced by the fund composition of the retirement savings plan. In 2 experiments, strong composition effects were observed, with a larger percentage of resources being invested in stock funds when more stock than bond funds were offered. Although participants changed their allocations repeatedly, the opportunity to learn did not alter the composition effects. Learning processes led to positive and negative recency effects as well, providing evidence that allocations were strongly influenced by the recent performance of the different allocation options. Two learning models were tested to explain these learning processes. The first, a local adaptation learning model, assumes that people change their behavior on the basis of recent experience, whereas the second, a reinforcement learning model, assumes that decisions are made on the basis of the totality of accumulated experience. The local adaptation model was more accurate in predicting allocation decisions, in explaining positive and negative recency effects, and in showing why composition effects are not overcome by learning.