YoVDO

Off-Policy Policy Optimization

Offered By: Simons Institute via YouTube

Tags

Reinforcement Learning Courses Deep Learning Courses Supervised Learning Courses Sequential Decision Making Courses

Course Description

Overview

Explore off-policy policy optimization in reinforcement learning with Dale Schuurmans from Google Brain and the University of Alberta in this 53-minute lecture. Delve into key concepts including the RL problem, batch policy optimization, and optimization objectives. Compare supervised and reinforcement learning approaches, and examine missing data inference in the context of sequential decision making. Gain insights into the emerging challenges in deep learning as applied to reinforcement learning algorithms and policy optimization techniques.

Syllabus

Intro
The RL problem
Batch policy optimization
Optimization objectives
Supervised vs reinforcement learning
Missing data inference
Sequential decision making
Sequential RL


Taught by

Simons Institute

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera 機器學習技法 (Machine Learning Techniques)
National Taiwan University via Coursera Machine Learning Capstone: An Intelligent Application with Deep Learning
University of Washington via Coursera Прикладные задачи анализа данных
Moscow Institute of Physics and Technology via Coursera Leading Ambitious Teaching and Learning
Microsoft via edX