The term Markov Decision Processes (MDP) belongs to the category of artificial intelligence and automation. A Markov Decision Process is a mathematical method used to solve complex decision problems, especially when many steps and uncertainties are involved. MDPs help computers and systems to make the best decision, even when it is not possible to predict what will happen next.
Imagine a robot in a warehouse that has to transport parcels from one place to another. It does not always know exactly how the environment will react to its actions. For example, a path may be blocked or it may suddenly rain. With Markov Decision Processes, the robot can learn which paths and actions make the most sense in the long term, even though it encounters new obstacles every time.
In short: Markov Decision Processes (MDP) make it possible for machines or programmes to make smart decisions in uncertain and changing situations. They are the basis for many modern applications, for example in robotics, autonomous driving or smart production lines.
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