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LCZero,
an adaptation of Gian-Carlo Pascutto's Leela Zero Go project ^[1] to Chess, using Stockfish's board representation and move generation. No heuristics or prior knowledge are carried over from Stockfish. The goal to build a strong UCT chess AI following the same type of deep learning techniques of AlphaZero as described in DeepMind's paper ^[2], but using distributed training for the weights of the deep residual convolutional neural network. The training process requires CUDA and a GPU accelerated version of Tensorflow installed ^[3].

See also

• AlphaZero
• Deep Learning
• UCT

Forum Posts

• Announcing lczero by Gary, CCC, January 09, 2018
  Re: Announcing lczero by Daniel Shawul, CCC, January 21, 2018 » Rollout Paradigm
• LCZero is learning by Gary, CCC, January 30, 2018
• LCZero update by Gary, CCC, March 14, 2018
  LCZero update (2) by Rein Halbersma, CCC, March 25, 2018
• LCZero: Progress and Scaling. Relation to CCRL Elo by Kai Laskos, CCC, March 28, 2018 » Playing Strength
• What does LCzero learn? by Uri Blass, CCC, April 05, 2018
• LCZero in Aquarium / Fritz by Carl Bicknell, CCC, April 11, 2018
• LCZero on 10x128 now by Gary, CCC, April 12, 2018
• lczero faq by Duncan Roberts, CCC, April 13, 2018

External Links

• LCZero
• GitHub - glinscott/leela-chess: A chess adaption of GCP's Leela Zero
• Breaking: Leela Chess Zero enters TCEC Season 12, Chessdom, April 18, 2018 » TCEC Season 11

References

1. ^ GitHub - gcp/leela-zero: Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper
2. ^ David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, Demis Hassabis (2017). Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. arXiv:1712.01815
3. ^ leela-chess/README.md at master · glinscott/leela-chess · GitHub

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