'Td learning' presentation slideshows

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Actor-Critic models: from ventral striatal reward-related activity to robotics simulations.

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From Reflex to Reason

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Reinforcement Learning I: prediction and classical conditioning

Reinforcement Learning I: prediction and classical conditioning. Peter Dayan Gatsby Computational Neuroscience Unit dayan@gatsby.ucl.ac.uk. (thanks to Yael Niv). Global plan. Reinforcement learning I: prediction classical conditioning dopamine Reinforcement learning II:

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Reinforcement Learning I: The setting and classical stochastic dynamic programming algorithms

Reinforcement Learning I: The setting and classical stochastic dynamic programming algorithms. Tuomas Sandholm Carnegie Mellon University Computer Science Department. passive. Learner. active. Reinforcement Learning (Ch. 17.1-17.3, Ch. 20). Sequential decision problems. Approaches :

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CS 182/CogSci110/Ling109 Spring 2008

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CS 188: Artificial Intelligence Spring 2007

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CS 188: Artificial Intelligence Spring 2007

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CS 188: Artificial Intelligence Spring 2007

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Meeting 9 - RL Wrap Up and B&W Tournament

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Dr. Itamar Arel College of Engineering Department of Electrical Engineering and Computer Science

ECE-517: Reinforcement Learning in Artificial Intelligence Lecture 10: Temporal-Difference Learning. October 6, 2011. Dr. Itamar Arel College of Engineering Department of Electrical Engineering and Computer Science The University of Tennessee Fall 2011.

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RL in the brain

RL in the brain. Nisheeth 24 th January 2019. Temporal difference learning. Consider the Q-learning update Or the SARSA update A generic temporal difference principle can be discerned for behavioral reinforcement. The TD learning principle.

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Dopamine, Uncertainty and TD Learning

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Backgammon

Players race to a) get all their men into their inner table, then b) move them to any imaginary point beyond their end point. Max 15 men per point. Backgammon.

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MDPs and the RL Problem

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CHAPTER 11 R EINFORCEMENT L EARNING VIA T EMPORAL D IFFERENCES

Slides for Introduction to Stochastic Search and Optimization ( ISSO ) by J. C. Spall. CHAPTER 11 R EINFORCEMENT L EARNING VIA T EMPORAL D IFFERENCES. Organization of chapter in ISSO Introduction Delayed reinforcement Basic temporal difference algorithm

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