alphago zero

1 Introduction The process of Alphago Zero (hereinafter referred to as zero) is shown in Figure A, B, in each state s, through MCTs search, to obtain the probability p of each possible move, where MCTs search adopts Self-play and executes the fθ strategy. Fθ mainly uses Microsoft's ResNet, that is, based on the residual learning. After using MCTs to obtain the pr

China IDC Circle June 3 reported that the DeepMind team (Google's) Alphago (a go AI) to 4:1 to win the top human professional chess player Li Shishi. How the hell did she play chess? Alphago in the face of the current chess game, she will simulate (deduce chess) n times, choose the "simulation" the most times to go, this is Alphago think of the best way. For exa

This topic will be about Alphago's past life, first of all, we explore the source of Alphago core technology, then we have David Silver and other people's two nature paper as the basis for the deconstruction Alphago and its upgraded version Alphago Zero. I have a limited level, if I have errors, I also hope to correct.

Innovation Factory chairman Lee Kai-fu in the Alphago and Li Shishi of the man-machine war, he said that four months ago Alphago defeated Li Shishi basically impossible, but this four months alphago progress a lot, the game should be very exciting. But whatever the outcome, the machine will surely triumph over mankind within 1-2 years. After the victory of mankin

A graphic alphago principle and weakness2016-03-23 Jeong Woo, Zhang Junbo ckdd Author Profile:Jeong Woo, PhD, editor-in-chief of ACM Transactions on Intelligent Systems and technology, ACM Data Mining China Chapter Secretary General.Zhang Junbo, PhD, member of ACM Data Mining China Branch, engaged in deep neural network related research.--------------------------------------Recently, Alphago in the man-mach

January 28, 2016, Google DeepMind on the nature announced that its AI go system Alphago historic victory over the human professional Weiqi player! This heavy news has undoubtedly caused the go field and the artificial intelligence field widespread attention! March Alphago against Li Shishi will attract the attention of all mankind! What makes the go algorithm produce a qualitative leap? To know, before

Tanaka, a researcher at Facebook Ai Group, updated an article in a column that detailed an analysis of Alphago's paper published in the journal Nature, which he said Alphago the entire system had a professional level even on a single machine, and that the game with Li Shishi would be quite exciting.The following is the original text of Dr. Tanaka's column:Recently I carefully read the next Alphago in the jo

AlphaGo is indeed a big eventTransferred from: HTTP://WWW.JIANSHU.COM/P/157A15DE47DFwords 3797 Read 696 comments 0 likes 4 Michael Nielsen, source address: https://www.quantamagazine.org/20160329-why-alphago-is-really-such-a-big-deal/ The Go program depicts the elements of human intuition, which is a progress that can have far-reaching effects. In 1997, IBM's Deep Blue system defeated the ch

This is DeepMind's paper on the January 28, 2016 Nature magazine, "Mastering the game of Go with deep neural networks and Tree Search", describes the AlphaGo program's Details. This blog post is a reading note on this article.AlphaGo Neural network structureAlphaGo is generally composed of two neural networks, the following I refer to them as "two Brains", which is not a reference in the original, but a metaphor for me.The role of the first brain (Pol

These days Alphago man-machine war stir in the limelight, to Google's AI made a big advertisement, is the Thunder out of it, there is a lot of AI to overcome all the "trend." And, like Afado, Alfa Cat and other new words continue to become a meal after tea people talk about the hot. As a tech man who studied in Japan, I also use the divergent thinking of overcoming machines to understand this hotspot for all programmers to think about.First, look at t

This is a creation in Article, where the information may have evolved or changed. These days Alphago man-machine war stir in the limelight, to Google's AI made a big advertisement, is the Thunder out of it, there is a lot of AI to overcome all the "trend." And, like Afado, Alfa Cat and other new words continue to become a meal after tea people talk about the hot. As a tech man who studied in Japan, I also use the divergent thinking of overcoming machi

Hardware configuration of the AlphagoRecently Alphago and Li Shishi in full swing, about the fourth set of Lee Shishi the hand is no longer within our scope of discussion. We focus on the following Alphago hardware configuration:Alphago has multiple versions, the strongest of which is the distributed version of Alphago. The distributed version (

May 23, "China Go Summit" in Wu Town, the world's first chess player Coger and Alphago Master's first game began at 10:30, 14:50, three chess game first, Alphago White 1/4 son wins, the score 0-1. Alphago at present in the strength has had the more obvious superiority, basically controls the entire game situation, has defeated the Coger smoothly. The new version

Copyright belongs to the author. Commercial reprint please contact the author to obtain authorization, non-commercial reprint please indicate the source. Author: Tanaka Link: http://zhuanlan.zhihu.com/yuandong/20607684 Source: Know Recently, I took a close look at the article published by Alphago in the journal Nature, writing some analysis to share with you. Alphago This system consists mainly of sever

The recent blaze of the Alphago, which DeepMind has open source, can be downloaded to GitHub Https://github.com/deepmind/lab, online and a python-based open source Alphago, which is not Google. By looking at the DeepMind source code, we can know that Alphago is using C + + and LUA scenarios. Of course, language is not the focus of

decision tree is very mysterious, but I think the decision tree should still use the idea like search, violent to find out where the best chance of winning. It takes full advantage of the speed of computer computing is very fast, but this brute force algorithm is not able to support the go AI, because the most places on the board of Weiqi 19*19 for the computer is feasible next, it is difficult to imagine its time complexity will be how spectacular.Remember that year six years old, when my moth

Is self-play a bottleneck in theory for AlphaGo to improve? My Perspective is not! The real problem with AlphaGo (and any other AI and human) are the state space of Go are much larger than the state space of Its neural network, therefore no matter how we train it, it still suffers from the underfitting problem. Which means there is always a problem with the value network and Policy network that, when some c

simply introduced here, interested in the Internet can find other information. Before Alphago out, the strongest go AI is based on MCTs, Alphago also used the MCTs method plus neural network optimization, and finally completed the victory of human professional players feat. structure Before learning the Alphago algorithm, it is necessary to have a general under