Artificial Intelligence, Reinforcement Learning, Machine Learning, Neural Networks, Markov Chains.
substitute G(t+1) with time step, t+1 as the starting point. Since the Bellman Equation is actually linear, we know that 𝔼(aX+bY)= a𝔼(X) +b𝔼(Y) which means the projected value of G(t+1) indicates the value of the state S(t+1) Let’s summarize with the final formula. The Bellman Equation basically