In a reinforcement learning process, a policy is updated. For a specific state-action pair, the probability of selecting the action under the original policy was 0.2. After the update, the probability of selecting the same action in the same state under the new policy is 0.5. Based on the relationship between these two probabilities, what can be inferred about the policy update for this specific action?

Evaluating a Policy Update for a Chatbot

Consider a reinforcement learning agent being trained. For a specific state-action pair, the ratio of the action's probability under the newly updated policy to its probability under the original reference policy is calculated to be 0.75. This result signifies that the training update has made the agent more likely to select this action in the future.