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Reinforcement Learning Part 1/2 (CS 188)

Pieter Abbeel UC Berkeley

Professor

1:25:00·2018·undergraduate level

This session introduces fundamental concepts of Reinforcement Learning, differentiating between model-based and model-free approaches, and detailing passive RL techniques like Direct Evaluation and Temporal Difference Learning.

AI & ML Reinforcement Learning Model-Based Learning Temporal Difference Learning Q-Learning

COMPSCI 188, LEC 001 - Fall 2018

COMPSCI 188, LEC 001 - Pieter Abbeel, Daniel Klein

Copyright @2018 UC Regents; all rights reserved

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Markov Decision Processes (MDPs) Part 2/2 (CS 188)

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Reinforcement Learning Part 2/2 (CS 188)

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Part of course22 lectures

CS 188: Introduction to Artificial Intelligence

Prof. Pieter Abbeel

Uninformed and A* heuristic search, constraint satisfaction, adversarial minimax/expectimax games, Markov decision processes, reinforcement learning, Bayes nets, and particle filtering.

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