- See Also
-
Links
- “The Value of Chess Squares”, Gupta et al 2023
- “Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
- “ChessGPT: Bridging Policy Learning and Language Modeling”, Feng et al 2023
- “Indoor Air Quality and Strategic Decision Making”, Künn et al 2023
- “AI, Ageing and Brain-Work Productivity: Technological Change in Professional Japanese Chess”, Yamamura & Hayashi 2022
- “Modeling Strong and Human-Like Gameplay With KL-Regularized Search”, Jacob et al 2021
- “Acquisition of Chess Knowledge in AlphaZero”, McGrath et al 2021
- “Vector Quantized Models for Planning”, Ozair et al 2021
- “Learning Chess Blindfolded: Evaluating Language Models on State Tracking”, Toshniwal et al 2021
- “NNUE: The Neural Network of the Stockfish Chess Engine”, Goucher 2021
- “Assessing Game Balance With AlphaZero: Exploring Alternative Rule Sets in Chess”, Tomašev et al 2020
- “Learning Personalized Models of Human Behavior in Chess”, McIlroy-Young et al 2020
- “Measuring Hardware Overhang”, hippke 2020
- “The Chess Transformer: Mastering Play Using Generative Language Models”, Noever et al 2020
- “Aligning Superhuman AI With Human Behavior: Chess As a Model System”, McIlroy-Young et al 2020
- “Smerdon Beats Komodo 5-1 With Knight Odds”, Doggers 2020
- “Transformers Play Chess”, Cheng 2020
- “A Very Unlikely Chess Game”, Alexander 2020
- “MuZero: Mastering Atari, Go, Chess and Shogi by Planning With a Learned Model”, Schrittwieser et al 2019
- “A General Reinforcement Learning Algorithm That Masters Chess, Shogi, and Go through Self-play”, Silver et al 2018
- “Learning to Play Chess With Minimal Lookahead and Deep Value Neural Networks”, Sabatelli 2017 (page 3)
- “Assessing Human Error Against a Benchmark of Perfection”, Anderson et al 2016
- “Giraffe: Using Deep Reinforcement Learning to Play Chess”, Lai 2015
- “Algorithmic Progress in Six Domains”, Grace 2013
- “When Will Computer Hardware Match the Human Brain?”, Moravec 1998
- “Human Window on the World”, Michie 1985
- “Turing-Complete Chess Computation”
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“The Value of Chess Squares”, Gupta et al 2023
“Evaluating Superhuman Models With Consistency Checks”, Fluri et al 2023
“ChessGPT: Bridging Policy Learning and Language Modeling”, Feng et al 2023
“Indoor Air Quality and Strategic Decision Making”, Künn et al 2023
“AI, Ageing and Brain-Work Productivity: Technological Change in Professional Japanese Chess”, Yamamura & Hayashi 2022
“AI, Ageing and Brain-Work Productivity: Technological Change in Professional Japanese Chess”
“Modeling Strong and Human-Like Gameplay With KL-Regularized Search”, Jacob et al 2021
“Modeling Strong and Human-Like Gameplay with KL-Regularized Search”
“Acquisition of Chess Knowledge in AlphaZero”, McGrath et al 2021
“Vector Quantized Models for Planning”, Ozair et al 2021
“Learning Chess Blindfolded: Evaluating Language Models on State Tracking”, Toshniwal et al 2021
“Learning Chess Blindfolded: Evaluating Language Models on State Tracking”
“NNUE: The Neural Network of the Stockfish Chess Engine”, Goucher 2021
“Assessing Game Balance With AlphaZero: Exploring Alternative Rule Sets in Chess”, Tomašev et al 2020
“Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess”
“Learning Personalized Models of Human Behavior in Chess”, McIlroy-Young et al 2020
“Measuring Hardware Overhang”, hippke 2020
“The Chess Transformer: Mastering Play Using Generative Language Models”, Noever et al 2020
“The Chess Transformer: Mastering Play using Generative Language Models”
“Aligning Superhuman AI With Human Behavior: Chess As a Model System”, McIlroy-Young et al 2020
“Aligning Superhuman AI with Human Behavior: Chess as a Model System”
“Smerdon Beats Komodo 5-1 With Knight Odds”, Doggers 2020
“Transformers Play Chess”, Cheng 2020
“A Very Unlikely Chess Game”, Alexander 2020
“MuZero: Mastering Atari, Go, Chess and Shogi by Planning With a Learned Model”, Schrittwieser et al 2019
“MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model”
“A General Reinforcement Learning Algorithm That Masters Chess, Shogi, and Go through Self-play”, Silver et al 2018
“A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play”
“Learning to Play Chess With Minimal Lookahead and Deep Value Neural Networks”, Sabatelli 2017 (page 3)
“Learning to Play Chess with Minimal Lookahead and Deep Value Neural Networks”
“Assessing Human Error Against a Benchmark of Perfection”, Anderson et al 2016
“Giraffe: Using Deep Reinforcement Learning to Play Chess”, Lai 2015
“Algorithmic Progress in Six Domains”, Grace 2013
“When Will Computer Hardware Match the Human Brain?”, Moravec 1998
“Human Window on the World”, Michie 1985
“Turing-Complete Chess Computation”
Wikipedia
Miscellaneous
-
http://rjlipton.wordpress.com/2014/12/28/the-new-chess-world-champion/ -
http://www.infinitychess.com/Page/Public/Article/DefaultArticle.aspx?id=118 -
https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/ -
https://cacm.acm.org/magazines/2022/2/258230-reimagining-chess-with-alphazero/fulltext -
https://en.chessbase.com/post/better-than-an-engine-leonardo-ljubicic-1-2 -
https://en.chessbase.com/post/better-than-an-engine-leonardo-ljubicic-2-2 -
https://en.chessbase.com/post/komodo-8-the-smartphone-vs-desktop-challenge -
https://en.chessbase.com/post/leela-chess-zero-alphazero-for-the-pc -
https://twitter.com/kenshinsamurai9/status/1662510532585291779 -
https://villekuosmanen.medium.com/i-played-chess-against-chatgpt-4-and-lost-c5798a9049ca -
https://www.lesswrong.com/posts/6dn6hnFRgqqWJbwk9/deception-chess-game-1 -
https://www.lesswrong.com/posts/Q3XaZTExzDpCLr4wu/efficiency-and-resource-use-scaling-parity -
https://www.lesswrong.com/posts/odtMt7zbMuuyavaZB/when-do-brains-beat-brawn-in-chess-an-experiment -
https://www.nybooks.com/articles/2010/02/11/the-chess-master-and-the-computer/ -
https://www.techrepublic.com/article/the-role-of-computers-in-planning-chess-strategy/
Link Bibliography
-
https://pubsonline.informs.org/doi/10.1287/mnsc.2022.4643: “Indoor Air Quality and Strategic Decision Making”, Steffen Künn, Juan Palacios, Nico Pestel -
https://arxiv.org/abs/2111.09259#deepmind: “Acquisition of Chess Knowledge in AlphaZero”, -
https://arxiv.org/abs/2106.04615#deepmind: “Vector Quantized Models for Planning”, Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals -
https://www.chess.com/news/view/smerdon-beats-komodo-5-1-with-knight-odds: “Smerdon Beats Komodo 5-1 With Knight Odds”, Peter Doggers -
https://github.com/ricsonc/transformers-play-chess/blob/master/README.md: “Transformers Play Chess”, Ricson Cheng -
https://slatestarcodex.com/2020/01/06/a-very-unlikely-chess-game/: “A Very Unlikely Chess Game”, Scott Alexander -
2017-sabatelli.pdf#page=3: “Learning to Play Chess With Minimal Lookahead and Deep Value Neural Networks”, Matthia Sabatelli