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 make the best decision even when it's unpredictable what will happen next.
Imagine a robot in a warehouse tasked with moving packages from one place to another. The robot doesn't always know exactly how the environment will react to its actions. For example, a path might be blocked, or it might suddenly start raining. With Markov Decision Processes, the robot can learn which paths and actions are most sensible in the long run, even though it encounters new obstacles every time.
In short: Markov Decision Processes (MDPs) enable machines or programmes to make clever decisions in uncertain and changing situations. They form the basis for many modern applications, such as in robotics, autonomous driving, or for smart manufacturing lines.
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