Connor McMonigle
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- Forum Posts
- 2020
- Re: Speculations about NNUE development (was New engine releases 2020) by Connor McMonigle, CCC, November 12, 2020 2021
- External Links
- References
Home * People * Connor McMonigle
Connor McMonigle [1] Connor McMonigle,
an American computer science major at the University of Washington and member of its Advanced Robotics team [2]. He is author of the UCI compliant open source chess engine Seer using a custom NNUE implementation, first released in October 2020 [3]. His GitHub repository further provides a C++ template based neural network reference implementation [4], and the cartesian-gp-chess-engine, an experiment involving evolving cartesian genetic programs to evaluate chess positions, using self play to evolve slightly superior chess playing cartesian programs each generation [5].
Forum Posts
2020
- Re: New engine releases 2020 by Connor McMonigle, CCC, October 18, 2020 » Seer 1.0
- Re: NiCimEngine Public release! by Connor McMonigle, CCC, October 28, 2020
- Re: Seer by Connor McMonigle, CCC, November 02, 2020 » Seer 1.1
- Re: New engine releases 2020 by Connor McMonigle, CCC, November 02, 2020 » Seer 1.1
- Re: Minic version 3 by Connor McMonigle, CCC, November 03, 2020 » Minic 3 [6]
- Re: Speculations about NNUE development (was New engine releases 2020) by Connor McMonigle, CCC, November 12, 2020 » Dragon by Komodo Chess, Halogen, Seer
Re: Speculations about NNUE development (was New engine releases 2020) by Connor McMonigle, CCC, November 12, 2020 2021
- Re: will Tcec allow Stockfish with a Leela net to play? by Connor McMonigle, CCC, June 17, 2021 » NNUE
External Links
References
- ↑ Advanced Robotics at University of Washington Team
- ↑ Advanced Robotics at University of Washington Team
- ↑ Re: New engine releases 2020 by Connor McMonigle, CCC, October 18, 2020
- ↑ GitHub - connormcmonigle/reference-neural-network
- ↑ GitHub - connormcmonigle/cartesian-gp-chess-engine: Experiment involving evolving cartesian genetic programs to evaluate chess positions
- ↑ Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger (2016). Densely Connected Convolutional Networks. arXiv:1608.06993
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