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  1. Did Alphago zero actually beat Alphago 100 games to 0?

    Oct 21, 2020 · 2 tl;dr Did AlphaGo and AlphaGo play 100 repetitions of the same sequence of boards, or were there 100 different games? Background: Alphago was the first superhuman go player, but it …

  2. Newest 'alphago' Questions - Artificial Intelligence Stack Exchange

    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 …

  3. AlphaGo (and other game programs using reinforcement-learning) …

    Apr 10, 2016 · The program AlphaGo has been built using, among other things (Monte-Carlo exploration of trees, etc.), neural networks which are trained from a huge database of human-played go games, …

  4. Difference between AlphaGo's policy network and value network

    Mar 29, 2016 · If anyone else stumbles upon this old question, like me, you'll be pleased to know that AlphaGo's successor, "AlphaGo Zero", as well as its successor "AlphaZero" do indeed get rid of the …

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

    Apr 9, 2019 · The paper that introduced AlphaGo, Mastering the game of Go with deep neural networks and tree search, motivates the use of MCTS Monte Carlo tree search (MCTS) uses Monte Carlo …

  6. What is the significance of move 37? (to a non go player)

    Feb 26, 2023 · 1 I have seen (and googled) information for Game 2, Move 37 in the AlphaGo vs. Lee Sedol match However it is difficult to find information concerning this move that doesn't rely on an …

  7. Would AlphaGo Zero become perfect with enough training time?

    The difference between AlphaGo Zero and a more traditional game search algorithm is to do with optimal use of available computing resources, as set by available hardware, training time and …

  8. What is the difference between DQN and AlphaGo Zero?

    The earlier AlphaGo version had 4 separate networks, 3 variations of policy network - used during play at different stages of planning - and one value network. Is designed around self-play

  9. policies - What kind of reinforcement learning method does AlphaGo ...

    Dec 23, 2020 · 3 In reinforcement learning, there are model-based versus model-free methods. Within model-based ones, there are policy-based and value-based methods. AlphaGo Deepmind RL model …

  10. Is it fair to compare AlphaGo with a Human player?

    Feb 3, 2018 · Is it fair to compare AlphaGo with a Human player? Depends on the purpose of the comparison. If we are comparing ability to win a game of Go, then yes. If we are comparing learning …