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Introduction to Reinforcement Learning (RL)

Introduction to Reinforcement Learning (RL)Billy Okal Apple is RLReinforcement Learning is a paradigm for Learning to make a good sequence of decisionsReinforcement Learning in Context4 Unsupervised LearningSupervised LearningLabels for all samplesNo labelsReinforcement LearningSparse & delayed labelsReinforcement Learning in Context5 Unsupervised LearningSupervised LearningReinforcement LearningData OptimizationData OptimizationData Optimization Long-term consequences ExplorationRL agent takes an action in an environment environment responds with a feedback signal agent uses the feedback to decide on future actions6 Example applications of RL Games Go, video console games Robotics drone, mobile robot navigation Medicine administering trials Dialogue systems, chatbots Personalized web internet ads, news feeds Finance trading Process optimization DRAM, elevator dispatch 7 Example applications of RL TD-Gammon for the game backgammon Early 90s8366 CHAPTER 16.

Introduction to Reinforcement Learning (RL) Billy Okal Apple Inc. What is RL. Reinforcement learning is a paradigm for learning to make a good sequence of decisions. Reinforcement Learning in Context 4 Unsupervised Learning Supervised Learning Labels for all samples No labels Reinforcement Learning Sparse & delayed labels.

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