Reinforcement learning
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Reinforcement learning is an approach for machine learning where an agent learns to take actions based on an environment from the concept of a reward.
The agent observes the world and learns to take actions to maximize a reward. This can be achieved by some form of exploration of the possible states.
Traditional examples of reinforcement learning include
Grid world
