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=== Aligning AI with humans === The Maia Chess project was began in 2020 by the [[University of Toronto]], [[Cornell University]], and [[Microsoft Research]]. Maia Chess is a [[Neural network (machine learning)|neural network]] constructed to impersonate a humanβs manner of playing chess based on skill. Each Maia models was tested on 9 sets of 500,000 positions each, covering rating levels from 1100 to 1900. They perform best when predicting moves made by players at their targeted rating level, with lower Maias accurately predicting moves from lower-rated players (around 1100) and higher Maias doing the same for higher-rated players (around 1900). The primary goal of Maia is to develop an AI chess engine that imitates human decision-making rather than focusing on optimal moves. Through personalization across different skill levels, Maia is able to simulate game styles typical for each level more accurately.<ref>@inproceedings{McIlroy_Young_2020, series={KDD β20}, title={Aligning Superhuman AI with Human Behavior: Chess as a Model System}, url={https://arxiv.org/abs/2006.01855}, DOI={10.1145/3394486.3403219}, booktitle={Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining}, publisher={ACM}, author={McIlroy-Young, Reid and Sen, Siddhartha and Kleinberg, Jon and Anderson, Ashton}, year={2020}, month=aug, pages={1677β1687}, collection={KDD β20} } </ref><ref name="ScienceFocusAIChess">{{cite web | url = https://www.sciencefocus.com/future-technology/ai-has-dominated-chess-for-25-years-but-now-it-wants-to-lose | title = AI has dominated chess for 25 years, but now it wants to lose | website = Science Focus | publisher = Immediate Media Company Ltd. | access-date = 2025-02-11 | date = 2023-02-13}}</ref>
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