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introduction to reinforcement LearningCS 294-112: Deep reinforcement LearningSergey LevineClass 1 is due next Wednesday! Remember that Monday is a holiday, so no office to start forming final project groups Final project assignment document and ideas document releasedToday s of a Markov decision of reinforcement learning of a RL overview of RL algorithm types Goals: Understand definitions & notation Understand the underlying reinforcement learning objective Get summary of possible algorithmsDefinitions1. run away2. ignore3. petTerminology & notationImages: Bojarskiet al. 16, NVIDIA trainingdatasupervisedlearningImitation LearningReward functionsDefinitionsAndrey MarkovDefinitionsAndrey MarkovRichard BellmanDefinitionsAndrey MarkovRichard BellmanDefinitionsThe goal of reinforcement learningwe ll come back to partially observed laterThe goal of reinforcement learningThe goal of reinforcement l

Introduction to Reinforcement Learning CS 285 Instructor: Sergey Levine UC Berkeley. Definitions. 1. run away 2. ignore 3. pet Terminology & notation. Images: Bojarski et al. 16, NVIDIA training data supervised learning Imitation Learning. Reward functions. Definitions Andrey Markov. Definitions Richard BellmanAndrey Markov.

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