Model Selection, Reinforcement Learning, Deep Learning.
term reward. Two policies used are i. Epsilon Greedy ii. Upper Confidence Bound Epsilon greedy Policy: Epsilon greedy is an exploration strategy in reinforcement learning. In epsilon greedy policy epsilon value in the range 0–1 is chosen. Given a list of actions, any of the actions is chosen with