I'm new to reinforcement learning. I'm studying DQN with decaying epsilon. I came across such example:
EPISODES = 91
GAMMA = 0.2
EPSILON_DECAY = 0.999
MIN_EPSILON = 0.01
MAX_EPSILON = 1
My questions are:
- Is it correct if epsilon doesn't reach MIN_EPSILON?
- Is there something wrong with the reward - the reward is not higher and higher but it is behaving otherwise - it decreases in time?