Difference between revisions of "Fat Fritz"
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'''Fat Fritz''',<br/> | '''Fat Fritz''',<br/> | ||
| − | a commercial chess entity by [[ChessBase]] | + | a commercial chess entity by [[ChessBase]] featuring a set of custom made [[Neural Networks|neural network]] weights that work in the open source project [[Leela Chess Zero]]. Initially announced as a cloud project inspired by [[DeepMind|DeepMind's]] ground breaking [[AlphaZero]] approach combining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) <ref>[[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''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815]</ref>, |
| − | Initially announced as a cloud project inspired by [[DeepMind|DeepMind's]] ground breaking [[AlphaZero]] approach combining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) <ref>[[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''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815]</ref>, | ||
further motivated by [[Albert Silver|Albert Silver's]] [[Deus X]] experience, relaxing the "Zero" paradigm of pure [[Reinforcement Learning|reinforcement learning]] due to [[Supervised Kearning|supervised learning]], Fat Fritz was released in November 2019 as part the [[Fritz|Fritz 17]] package, | further motivated by [[Albert Silver|Albert Silver's]] [[Deus X]] experience, relaxing the "Zero" paradigm of pure [[Reinforcement Learning|reinforcement learning]] due to [[Supervised Kearning|supervised learning]], Fat Fritz was released in November 2019 as part the [[Fritz|Fritz 17]] package, | ||
best supported by a [[GPU]] card such as [[Nvidia]] [https://en.wikipedia.org/wiki/GeForce_20_series GeForce 20 series]. | best supported by a [[GPU]] card such as [[Nvidia]] [https://en.wikipedia.org/wiki/GeForce_20_series GeForce 20 series]. | ||
Revision as of 01:00, 13 November 2019
Fat Fritz,
a commercial chess entity by ChessBase featuring a set of custom made neural network weights that work in the open source project Leela Chess Zero. Initially announced as a cloud project inspired by DeepMind's ground breaking AlphaZero approach combining Deep learning with Monte-Carlo Tree Search (MCTS) [1],
further motivated by Albert Silver's Deus X experience, relaxing the "Zero" paradigm of pure reinforcement learning due to supervised learning, Fat Fritz was released in November 2019 as part the Fritz 17 package,
best supported by a GPU card such as Nvidia GeForce 20 series.
The project was further discussed and supported by AlphaZero co-author Thore Graepel, German computer chess icon Thomas Nitsche along with his sons and Math42 authors Raphael Nitsche and Maxim Nitsche [2], and by Daniel Uranga [3].
See also
Forum Posts
- 'Deus X' Unveiled as FAT FRITZ PROJECT... by supersharp77, CCC, August 13, 2019
- Match between SF 10 and Fat Fritz by Steppenwolf, CCC, August 26, 2019
- Chessbase's Albert Silver on LC0 & Fat Fritz by supersharp77, CCC, August 26, 2019
- "Fat fritz" stronger than Stockfish ? by Mehdi Amini, CCC, September 24, 2019
- UCI Win/Draw/Loss reporting by Gian-Carlo Pascutto, CCC, October 22, 2019
- Fritz 17 by sainzlei, CCC, October 25, 2019
External Links
- Fat Fritz – What on Earth is that? by Albert Silver, ChessBase News, August 13, 2019
- Using Fat Fritz in the Engine Cloud by Nadja Wittmann, ChessBase News, August 15, 2019
- Standing on the shoulders of giants by Albert Silver, ChessBase News, September 18, 2019
- Introducing Fritz 17 with Fat Fritz and other goodies, ChessBase News, November 12, 2019
- GitHub - DanielUranga/lc0 at uci-wdl-reporting
- lc0 84 - AppVeyor
References
- ↑ 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
- ↑ Fat Fritz – What on Earth is that? by Albert Silver, ChessBase News, August 13, 2019
- ↑ GitHub - DanielUranga/lc0 at uci-wdl-reporting
