Radix
×

Reinforcement Learning

curated by Camillo

23 people already started

About this learning path

Reinforcement Learning

One of the three paradigms of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.

Reinforcement Learning comes from the learning path of Machine Learning . The learning path of Reinforcement Learning integrates concepts of Dynamic Programming which you should dive into.
The Reinforcement Learning path can be specialized into Deep Reinforcement Learning .
Reinforcement Learning is particulary useful for Robotics .

Part of this learning path

Dynamic Programming

Web resources
Start immediately and learn at your own pace.

Flexible schedule
Set and adhere to flexible deadlines.

Approx. 3 months to complete
Recommended 12 hours/week

Mostly English

Curator

Camillo Rohe curates
Reinforcement Learning

This How it Works

You work from module to module. In each module you'll find resources containing:

1. Information

2. Educational content

3. Places to exchange infos

4. Applications, Tools

( 5. Entertaining content )

After studying a resource, you check it.

Learning Path

Module

1

 

Model-free

Module

2

»

Reinforcement Learning Lectures

»

Reinforcement Learning: An Introduction Non-fictional

 

Gym Library

Module

3

»

State–action–reward–state–action (SARSA) Algorithm

»

Q-learning

»

Reinforcement Learning State-of-the-Art Non-fictional

»

Algorithms for Reinforcement Learning

 

Garage Toolkit

Module

4