I was having trouble with reinforcement learning and was looking for related resources, and I think I've finally understood it well enough thanks to this lecture.
I was especially satisfied with the two-step explanation for the practical exercises (flow, actual coding), and the debugging explanations of intermediate values were also very helpful.
Thank you.


okputto3340

Recently, all the remarkable achievements in the field of artificial intelligence are being announced in the area of reinforcement learning. This covers reinforcement learning technology—which is bringing about true innovation in AI such as robotics, autonomous driving, and humanoid machines—from basic to advanced levels in an easy-to-understand way for beginners.

trimurti

From Introduction to Reinforcement Learning to Deep Q-learning/Policy Gradient

이론과 실습 한 번에

이론 실습 모두

인공지능

Reinforcement Learning(RL)

강화학습

파이썬

파이토치

YoungJea Oh

입문

초급

중급이상

Python

Deep Learning(DL)

PyTorch

Preparing the educational environment

Reinforcement Learning Overview

MDP (Markov Decision Process)

Policy & Value Function

Dynamic Programming

Monte Carlo Method

Temporal Difference Learning

Prediction and Update Using Deep Q-learning

Policy Gradient

Implementing the policy gradient algorithm