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Questions tagged [alphago]

For questions related to DeepMind's AlphaGo, which is the first computer Go program to beat a human professional Go player without handicaps on a full-sized 19x19 board. AlphaGo was introduced in the paper "Mastering the game of Go with deep neural networks and tree search" (2016) by David Silver et al. There have been three more powerful successors of AlphaGo: AlphaGo Master, AlphaGo Zero and AlphaZero.

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1answer
124 views

Alphazero policy head loss not decreasing

I am now working on training an alphazero player for a board game. The implementation of board game is mine, MCTS for alphazero was taken elsewhere. Due to complexity of the game, it takes a much ...
3
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1answer
78 views

Why is Monte Carlo used as the tree search algorithm for AlphaGo?

Could a better algorithm other than Monte Carlo be used for the AlphaGo computer? Why didn't the DeepMind team think of choosing another kind of algorithm rather than spending time on their neural ...
2
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1answer
54 views

Similarities and differences between UCT algorithms in (i), (ii), (iii) and (iv)?

I am trying to understand the similarities and differences between: (i) the UCT algorithm in Kocsis and Szepesvári (2006); (ii) the UCT algorithm in Section 3.3 of Browne et al (2012); (iii) the MCTS ...
5
votes
1answer
58 views

Why didn't champion of the Go game manage to win the last game against AlphaGo, after winning the 4th one?

In the documentary about the match, it is said that after losing the 4th game, AlphaGo came back stronger and started to play in a weird way (not human-like) and it was pretty impossible to be beaten. ...
2
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0answers
27 views

Why is a constant plane of ones added into the input features of AlphaGo?

In the paper Mastering the game of Go with deep neural networks and tree search, the input features of the networks of AlphaGo contains a plane of constant ones and a plane of constant zeros, as ...
11
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2answers
842 views

Is AlphaZero an example of an AGI?

From DeepMind's research paper on arxiv.org: In this paper, we apply a similar but fully generic algorithm, which we call AlphaZero, to the games of chess and shogi as well as Go, without any ...
4
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2answers
392 views

AlphaZero Value Network

The Alpha Zero (as well as AlphaGo Zero) papers say they trained the value head of the network by "minimizing the error between the predicted winner and the game winner" throughout its many self play ...
6
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3answers
179 views

Would AlphaGo Zero become perfect with enough training time?

Would AlphaGo Zero become theoretically perfect with enough training time? If not, what would be the limiting factor? (By perfect, I mean it always wins the game if possible, even against another ...
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0answers
85 views

How will AlphaGo be implemented in Tensorflow.js?

AlphaGo is eventually going to be implemented in Tensorflow.js. How to tackle the change of functionality that the new JavaScript language will bring?
1
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0answers
58 views

How basically AI synthesize thinking?

In the instance like AlphaGo Zero. How N' why AlphaGo Zero's training is so stable? Compared with traditional game theory applied in Deep RN technique!? How "AlphaGo Zero" differs from "...
5
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1answer
310 views

How does one code the rules of a boardgame for deep learning?

When Google researchers created AlphaGo, how did they simulate the game of Go? If I wanted to take the same approach to other games, like Risk, how would I go about coding the rules of the game? Is ...
2
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5answers
193 views

Is it fair to compare AlphaGo with a Human player?

A human player plays limited games compared to a system that undergoes millions of iterations. Is it really fair to compare AlphaGo with the world #1 player when we know experience increases with the ...