It is a feedback-based process, in which an AI agent (A software component) automatically explores its surroundings by hitting & trial, taking action, learning from experiences, and improving its performance. Agent gets rewarded for each good action and get punished for each bad action; hence the goal of reinforcement learning agent is to maximize the rewards.
In reinforcement learning, there is no labeled data like supervised learning, and agents learn from their experiences only. We use reinforcement learning much in robotics.
So reinforcement learning applied to automate mario game will look like-
Taking you to the next exercise in seconds...
Want to create exercises like this yourself? Click here.
No hints are availble for this assesment
Answer is not availble for this assesment
Please login to comment
Be the first one to comment!