Feb 26, 2023 · 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 …

Jun 8, 2020 · AlphaGo Zero only uses the black and white stones from the Go board as its input, whereas previous versions of AlphaGo included a small number of hand-engineered features. …

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 …

In the previous research, in 2015, Deep Q-Learning shows its great performance on single player Atari Games. But why do AlphaGo's researchers use CNN + MCTS instead of Deep Q …

Oct 14, 2022 · Finally, I recommend going over the AlphaGo paper first as it spells out more details (especially the value and policy network part), then AlphaGo Zero (which merges the …

Sep 25, 2023 · AlphaGo Zero uses a much simpler variant of the asynchronous policy and value MCTS algorithm (APV-MCTS) Multiple simulations are executed in parallel on separate search …

We can read on wiki page that in March 2016 AlphaGo AI lost its game (1 of 5) to Lee Sedol, a professional Go player. One article cite says: AlphaGo lost a game and we as researchers …

Mar 29, 2016 · I was reading a high level summary about Google's AlphaGo, and I came across the terms "policy network" and "value network". At a high level, I understand that the policy …

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 …

Dec 30, 2020 · From the AlphaGo Zero paper, during MCTS, statistics for each new node are initialized as such: ${N(s_L, a) = 0, W (s_L, a) = 0, Q(s_L, a) = 0, P (s_L, a) = p_a}$. The …