Abstract
Q-learning in reinforcement learning can serve as a useful tool in many fields. The one popular technology one can hear lately is artificial intelligence, which can be found in almost any field and area. However, artificial intelligence is a combination of different technologies and methods that are most of the time ignored or overshadowed. Q-learning is a method in which each action or step is analyzed and provided by feedback. Depending on the feedback the method continues its actions by choosing the best possible path. In this paper, Q-learning will be briefly expanded with the examples. The main focus of this work will be on Its application in different fields. The following fields will be covered: healthcare, education, gaming, manufacturing, and finances.
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