Experience in a domain can sometimes offset cognitive declines that occur with aging. Using a series of neural network simulations of learning chess opening positions, the authors investigated how structured knowledge in a distributed representation may influence age-related declines. Aging manipulations implemented as modulations of neural noise showed increased knowledge as being protective of performance on a chess memory span task, whereas changes in neural plasticity and neural loss lead to main effects without interactions and steeper declines for the initially more able. The models could also simulate the increase in variability in older groups.