1. A method of managing data replacement in a cache, comprising: selecting, in accordance with a selection process, one of multiple data replacement protocols for evicting data from the cache, wherein the selection process has a biasing that is adjustable to change the probability of selecting any of the data replacement protocols relative to the others; evicting data from the cache using the selected data replacement protocol; detecting a hit rate of the cache in response to the selected data replacement protocol; and adjusting the biasing of the selection process in response to the detected hit rate of the cache after selecting the selected data replacement protocol, to vary the probability that the selected data replacement protocol will later be selected according to the selection process when subsequently selecting in one of the data replacement protocols for evicting data from the cache, wherein the acts of selecting and adjusting are conducted in accordance with a SARSA (State-Action-Reward-State-Action) λ reinforcement learning technique, wherein the SARSA λ reinforcement learning technique defines multiple state-action pairs, wherein each state-action pair is a concurrence of a particular cache hit rate (state) with a particular data replacement protocol selection (action).