AI & Machine Learning

Stop Coding the AI, Code the World: A Simple Guide to Markov Decision Processes

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Markov Decision Processes (MDPs) provide a mathematical framework for Reinforcement Learning, enabling agents to learn through trial and error rather than being programmed with specific instructions. This approach is crucial because it allows AI systems to adapt to complex, unpredictable environments by focusing on current state transitions and rewards, making the learning process more efficient and scalable.

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