Questions tagged [alphago-zero]

For questions related to AlphaGo Zero, which is a version of DeepMind's Go software, AlphaGo, that does not use data from human games and it is stronger than AlphaGo. There is a generalized version of AlphaGo Zero called AlphaZero, which beat the 3-day version of AlphaGo Zero by winning 60 games to 40. AlphaGo Zero was introduced in the paper "Mastering the game of Go without human knowledge" (2017) by David Silver et al.

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Why does the policy network in AlphaZero work?

In AlphaZero, the policy network (or head of the network) maps game states to a distribution of the likelihood of taking each action. This distribution covers all possible actions from that state. ...
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1answer
854 views

Why is the merged neural network of AlphaGo Zero more efficient than two separate neural networks?

AlphaGo Zero contains several improvements compared to its predecessors. Architectural details of Alpha Go Zero can be seen in this cheat sheet. One of those improvements is using a single neural ...
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3answers
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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 ...
5
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2answers
822 views

What is the difference between DQN and AlphaGo Zero?

I have already implemented a relatively simple DQN on Pacman. Now I would like to clearly understand the difference between a DQN and the techniques used by AlphaGo zero/AlphaZero and I couldn't find ...
4
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2answers
472 views

What part of the game is the value network trained to predict a winner on?

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 ...
3
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1answer
136 views

How Does AlphaGo Zero Implement Reinforcement Learning?

AlphaGo Zero (https://deepmind.com/blog/alphago-zero-learning-scratch/) has several key components that contribute to it's success: A Monte Carlo Tree Search Algorithm that allows it to better search ...
3
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1answer
72 views

What is the input to AlphaGo's neural network?

I have been reading an article on AlphaGo and one sentence confused me a little bit, because I'm not sure what it exactly means. The article says: AlphaGo Zero only uses the black and white stones ...
3
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1answer
97 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 ...
3
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0answers
107 views

How is the rollout from the MCTS implemented in both of the AlphaGo Zero and the AlphaZero algorithms?

In a vanilla Monte Carlo tree search (MCTS) implementation, the rollout is usually implemented following a uniform random policy, that is, it takes random actions until the game is finished and only ...
2
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1answer
65 views

Why does AlphaGo Zero select move based on exponentiated visit count?

From the AlphaGo Zero paper, AlphaGo Zero uses an exponentiated visit count from the tree search. Why use visit count instead of the mean action value $Q(s, a)$?
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1answer
31 views

How do the achievements met in the gaming field (ex. AlphaGo Zero) impact other fields of application?

How can we use the ability of AlphaGo Zero computer, to do something in any other life important related field? Is it possible to make something important besides having created something so smart ...
2
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0answers
48 views

AlphaGo Zero: Does the policy head give a probability for every possible move?

If I understood correctly, the AlphaGo Zero network returns two values: a vector of logit probabilities p and a value v. My question is: in this vector that it is outputted, do we have a probability ...
2
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0answers
42 views

Alphazero Value loss doesn't decrease

Currenly I'm trying to reimplement alphazero in pure c++ using libtorch to accomodate my project's need. But when I training my model, I found out that the value loss doesn't decrese at all after even ...
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1answer
61 views

How does the AlphaGo Zero policy decide what move to execute?

I was going through the AlphaGo Zero paper and I was trying to understand everything, but I just can't figure out this one formula: $$ \pi(a \mid s_0) = \frac{N(s_0, a)^{\frac{1}{\tau}}}{\sum_b N(s_0,...
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1answer
171 views

How should I interpret the weights file of the Leela Zero neural network?

I am trying to understand the NN (Neural Network) architecture given at https://github.com/leela-zero/leela-zero/blob/next/training/caffe/zero.prototxt. So, I downloaded the NN weights from https://...
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0answers
60 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 "...
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0answers
54 views

Total loss increasing, but loss components are decreasing?

I am writing a AlphaGo Zero clone, and sometimes in the training the policy head loss and value head loss would both be decreasing, but the total loss is increasing? How is this possible? I am using ...
0
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0answers
57 views

How AlphaGo Zero is learning from $\pi_t$ when $z_t = -1$?

I have questions on the way AlphaGo Zero is trained. From original AlphaGo Zero paper, I knew that AlphaGo Zero agent learns a policy, value functions by the gathered data $\{(s_t, \pi_t, z_t)\}$ ...
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0answers
30 views

How does (or should) AlphaGoZero (which does chess) fare against Deep Blue?

Deep blue is good at chess, but is more "hand-coded" or "top-down". https://en.wikipedia.org/wiki/Deep_Blue_(chess_computer) AlphaGoZero is "self-taught", and at Go is very much super-human. https://...