# Reinforcement learning

tags
Machine learning

In reinforcement learning, agents take actions within an environment. Usually, both the agent and environment states change in reaction to this action. A reward is given to the agent to tell it if the action was positive or negative.

The goal of a learning agent is to act so as to maximize that reward.

An agent can be anything from a fixed set of if-else statements to a deep neural network.

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