Oct 19, 2017 ¡¤ Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules.

An artificial-intelligence program called AlphaGo Zero has mastered the game of Go without any human data or guidance.

We introduce a new approach to computer Go that uses value networks to evaluate board positions and policy networks to select moves. These deep neural networks.

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains.

Oct 19, 2017 ¡¤ Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in ...

Feb 25, 2019 ¡¤ Toronto Deep Learning Series For slides and more information, visit https://tdls.a-i.science ...
Duration: 1:14:03
Posted: Feb 25, 2019

Oct 18, 2017 ¡¤ Yeah, it's like an AlphaGo that's just gone Super Saiyan 3. The version that beat Jie and Sedol didn't beat it even once.

It is trained solely by self-play reinforcement learning, starting from random play, without any supervision or use of human data.

Apr 1, 2023 ¡¤ AlphaGo was the first system to achieve superhuman performance in Go. Its predecessor, AlphaGo Zero, won 100–0 against the previously published champion ...

Start with 19x19 empty board. One player take black stones and the other take white stones. Two players take turns to put stones on the board.