In December-2017 KDnuggets published an interview with Rich Sutton, the father of Reinforcement Learning. “Reinforcement learning is learning from rewards, by trial and error, during normal interaction with the world. This makes it very much like natural learning processes and unlike supervised learning, in which learning only happens during a special training phase in which a supervisory or teaching signal is available that will not be available during normal use.”
For example, speech recognition is currently done by supervised learning, using large datasets of speech sounds and their correct transcriptions into words. The transcriptions are the supervisory signals that will not be available when new speech sounds come in to be recognized. Game playing, on the other hand, is often done by reinforcement learning, using the outcome of the game as a reward. Even when you play a new game you will see whether you win or lose, and can use this with reinforcement learning algorithms to improve your play. Read more
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