What is Reinforcement Learning?

Reinforcement learning is a Machine Learning field that allows you to take suitable actions in specific situations to maximize rewards. This technology trains machines to learn several models and make important decisions. Further, the main concern of this method is how software agents take certain actions and make decisions in the given environment.

In the case of reinforcement learning, the solution is not given prior. However, reinforcement agents simply decide what needs to be done to perform a given task. Since there is no dataset available for training, this method allows machines to learn from their own experience. Further, the software agents in reinforcement learning are rewarded for their positive behavior, thereby encouraging these actions; whereas, for any negative behavior, they are punished. Their ultimate goal is to learn the required behavior by maximizing their overall reward.

Now that you have briefly understood what reinforcement learning is, let’s take a look at some of its applications in various domains and understand its use.

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Reinforcement Learning Applications

After getting detailed knowledge of reinforcement learning, let’s discuss some of its applications in domains such as gaming, healthcare, robotics, digital marketing, and more.

Applications of Reinforcement Learning in Games

Gaming applications and reinforcement learning run hand-in-hand in most cases. Gaming applications are a challenging domain that helps you test various reinforcement learning algorithms.

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