I have recently solved the Cartpole problem using double deep Q-learning. When I saw how the agent was doing, it used to go right every time, never left, and it did similar actions all the time.
Did the model overfit the environment? It seems that the agent just memorized the environment.
What are the common techniques to prevent the agent to overfit like that? Is that a common problem?