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TEST & PLAY IN OUR LAB
01

Grid World using Dynamic Programming is the easiest form of  Reinforcement Learning that uses Tabular Method.

02

In Monte Carlo method, the RL agent does not know anything about the environment dynamics. It had to discover it by itself.

03

A mixture of Dynamic Programming and Monte Carlo methods. It is considered a breakthrough in the RL approach.

04

Discover the importance of Exploration vs Exploitation dilemma in Reinforcement Learning.

05

Hands-on on Deep Reinforcement Learning

PUBLISHED ARTICLES
Dynamic Programming in Reinforcement Learning, the Easy Way
Dynamic Programming in Reinforcement Learning, the Easy Way
Monte Carlo in Reinforcement Learning, the Easy Way
Monte Carlo in Reinforcement Learning, the Easy Way
TD in Reinforcement Learning, the Easy Way
TD in Reinforcement Learning, the Easy Way
Q vs V in Reinforcement Learning, the Easy Way
Q vs V in Reinforcement Learning, the Easy Way
Basics of Reinforcement Learning, the Easy Way
Basics of Reinforcement Learning, the Easy Way
Gradient Descent, the Easy Way
Gradient Descent, the Easy Way
Summary of Tabular Methods in Reinforcement Learning
Summary of Tabular Methods in Reinforcement Learning
Double Q-Learning, the Easy Way
Double Q-Learning, the Easy Way
Back Propagation, the Easy Way (Part 1)
Back Propagation, the Easy Way (Part 1)
Back Propagation, the Easy Way (Part 2)
Back Propagation, the Easy Way (Part 2)
Back Propagation, the Easy Way (Part 3)
Back Propagation, the Easy Way (Part 3)
Math behind Reinforcement Learning, the easy way
Math behind Reinforcement Learning, the easy way
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    About us

    RL-LAB is an attempt to make Reinforcement Learning accessible to AI enthusiasts.
    Our objective is to make your Reinforcement Learning experience an enjoyable one-stop journey.

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