Q-Learning: Advancing various systems, including real and virtual environments – current and future states

Abstract

As we delve into the realm of artificial intelligence, we understand that the technology is diverse in the techniques it utilizes. these approaches are utilized to enhance the artificial intelligence depending on the tasks. each task requires a unique approach and hence must be dealt with individually, of course, most of the tasks require a complex approach and hence all methods must be implemented to achieve the best outcome of the task. the one approach that will be covered in this work is Q-learning. it is a component of the reinforcement method, which is a subpart of machine learning. this approach is used to explore dynamic environments. This approach is used in various fields and provides solid results. hence, the work will try to explain what is Q-leaning approach in reinforcement learning is and in which fields it is applicable. the focus will also be on its current state and its future perspectives.