Reinforcement Learning, Artificial Intelligence, Machine Learning, Data Science, Statistics.
state ‘s,’ assuming a stochastic policy, there are ’n’ possible actions according to π(a∣s). The value of state ‘s’ (total reward) is Rπ​(s), and for each action ‘a’ taken with probability π(a∣s), the q-value (total reward earned after taking ‘a’ from state ‘s’) is Rπ​(s,a). Mathematically, this