From Zero to Master in Hours: AlphaZero Accelerates Reinforcement Learning

Google’s DeepMind has once again surprised the machine learning community, this time with the introduction of AlphaZero — a new algorithm that can quickly surpass human board game performance through reinforcement learning self-play. It was was just two months that DeepMind published their Nature paper on AlphaGo Zero, which mastered the game of Go in

Deepmind AlphaZero - Mastering Games Without Human Knowledge

Self-play reinforcement learning in AlphaGo Zero. a The program plays a

Reinforcement Learning Reading Group – Page 3 – Reinforcement Learning Reading Group for the Parr Group and Associates

GitHub - adepierre/Caffe_AlphaZero: Implementation of Deepmind's AlphaZero algorithm with Caffe and C++

Deep Reinforcement Learning training

DeepMind, Google Brain & World Chess Champion Explore How AlphaZero Learns Chess Knowledge

PDF] Accelerating and Improving AlphaZero Using Population Based Training

PDF] Accelerating and Improving AlphaZero Using Population Based Training

How to get started with Reinforcement Learning (RL), by Aleksa Gordić

A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization - ScienceDirect

Reinforcement Learning – Silverton Consulting

Reinforcement Learning, Fast and Slow: Trends in Cognitive Sciences

Hallucinogenic Deep Reinforcement Learning Using Python and Keras, by David Foster, Applied Data Science

On its own, in just a few hours of experimental self-play, AlphaZero blew past a level of Chess mastery that took humans over 1,500 years to attain., by 13D Research