play alphago

, see the second picture below).According to these two grades of two chess players,Li Shishi the odds per disk is 89% (see formula: How to guide:converting Elo Differences to Winning probabilities:chess link address: https://www.reddit.com/r /chess/comments/2y6ezm/how_to_guide_converting_elo_differences_to/tips: To access this link to be copied and pasted into the browser open, the same below). If you play a game,

capabilities and work in areas where human experience is missing. In recent years, the use of intensive learning and training of the deep neural network has made rapid progress. These systems have surpassed the level of human players in video games, such as atari[6,7] and 3D virtual Games [8,9,10]. However, the most challenging areas of play in terms of human intelligence, such as Weiqi, are widely considered to be a major challenge in the field of A

sense, this is a move that does not search the future of the child and does not evaluate the result checkerboard state. To go beyond the amateur level, AlphaGo needs a way to measure the state of the chessboard.To overcome this obstacle, the designers have developed the core idea of AlphaGo--the strategy network and its own game, to obtain a given chessboard state is the probability of victory is estimated

level of chess. Value Network Global Analysis of the "brain": the use of self-learning to grow the "brain" study on the entire face of the face judgment, to achieve a global analysis of the entire game. So, Alphago's "brain" actually has four brain regions, each brain area function differently, but compared to find that these abilities basically for the human chess player to play the different thinking, including both local calculations, but

go to strengthen learning in this area. From the above analysis can also be seen, compared with the previous go system, alphago less dependent on the field of Weiqi knowledge, but still far from the extent of the general system. Professional chess players can understand the opponent's style and take a strategy after watching a few innings, a veteran gamer can play a new game a few times soon after the star

can achieve with a breakthrough. Behind the success, is the author, especially the two first author David Silver and Aja Huang, in the doctoral stage and after graduating five years of accumulation, not overnight can be completed. It is well deserved that they can make alphago and enjoy the present honor. From the above analysis can also be seen, compared to the previous go system, alphago less dependent o

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

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

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

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

Preface Recently read Alphago's paper: Mastering then Game of Go with Deep nerual Networks and Search. Amazed at the creativity of these people and the power of neural networks, the game of Weiqi can be done to this extent. Write a paper in the method and their own thinking it, this article is basically a thesis in the view, but to my perspective to read, there are errors in the place to welcome. about chessboard chess game Remember when in college, the school held an artificial intelligence 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

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

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 (

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.Go is a zero-sum perfect information game, 0

Author | Joshua Greavescompiling | Liu Chang, Lin Yu 眄 This paper is the most important content in the book "Reinforcement Learning:an Introduction", which aims to introduce the basic concept and principle of learning reinforcement learning, so that readers can realize the newest model as soon as possible. After all, for any machine-learning practitioner, RL (intensive learning, i.e. reinforcement Learning) is a very useful tool, especially in the Shinang of