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Sample-based Learning Methods

Teacher

Martha White

Position

Reviews

4.8/5
4.8

Tutorial Price

$
https://www.coursera.org/learn/sample-based-learning-methods

Level

NYR

Duration

NYR

# of Reviews

546

Module Type

On demand video

In this course, you will learn about several algorithms that can learn near optimal policies based on trial and error interaction with the environment---learning from the agent’s own experience. Learning from actual experience is striking because it requires no prior knowledge of the environment’s dynamics, yet can still attain optimal behavior. We will cover intuitively simple but powerful Monte Carlo methods, and temporal difference learning methods including Q-learning. We will wrap up this course investigating how we can get the best of both worlds: algorithms that can combine model-based planning (similar to dynamic programming) and temporal difference updates to radically accelerate learning.

Instructors

Martha White

Link to Course

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