What is overfitting in the context of reinforcement learning?
a) When the agent only learns specific situations and fails to generalize
b) When the agent learns the optimal policy
c) When the agent explores all possible states
d) When the agent reaches the terminal state
Answer:
a) When the agent only learns specific situations and fails to generalize
Explanation:
Overfitting in reinforcement learning occurs when an agent becomes too specialized in certain scenarios and struggles to perform well in new or unseen situations.
Reference:
Reinforcement Learning (RL) Quiz – MCQ Questions and Answers