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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, NVIDIAtrainingdatasupervisedlearningImit ation 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 lea

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.

  Introduction, Learning, Reinforcement, Introduction to reinforcement learning