2024-actions-and-consequences-the-science-of-robot-learning

2024/Actions and Consequences: The Science of Robot Learning/article.md

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+# Actions and Consequences: The Science of Robot Learning
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+Pavlov, a Russian scientist, figured out you can trick a dog into drooling with a bell. At first, the bell was just noise—no drool, no reaction. But Pavlov kept ringing it and giving the dog food right after. Eventually, the dog thought, "Bell = snacks!" and started drooling every time it heard the bell, food or not. Basically, Pavlov turned a bell into a dinner bell. Behavior was officially hacked!
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+Now imagine teaching robots or computers in a similar way. Reinforcement Learning is a way of teaching computers or robots to learn by trying things out and improving based on feedback. The system takes an action and gets a reward if the action was good or a penalty if it was bad. Over time, it learns to choose actions that get the most rewards and avoid penalties. This method helps it figure out the best way to solve a problem by learning from its own successes and mistakes.
+## Authors
+- Subahini Nadarajh