Artificial Intelligence, Machine Learning, Data Science, Reinforcement Learning, OpenAI.
discounted_reward to loss = -1 x Σlog(probability) x (Reward+γV(S`)-V(S)) And for DQN it remains Mean Squared Error. hence the final loss: -1 x Σlog(probability)x(Reward+γV(S`)-V(S))+MSE(Actual_V(S),Predicted_V(S)) where the term (Reward+γV(S`)-V(S)) comes from the State-Value Network which is