Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
rewards or nonstationary environments. The balance between exploration and exploitation is crucial in reinforcement learning, even in deterministic or stationary cases. incremental implementation The text discusses incremental implementation methods for estimating action values as sample averages