Corpus ID: 221266730

Learning Personalized Models of Human Behavior in Chess

@article{McIlroyYoung2020LearningPM,
  title={Learning Personalized Models of Human Behavior in Chess},
  author={Reid McIlroy-Young and Russell Wang and S. Sen and J. Kleinberg and A. Anderson},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.10086}
}
  • Reid McIlroy-Young, Russell Wang, +2 authors A. Anderson
  • Published 2020
  • Computer Science
  • ArXiv
  • Even when machine learning systems surpass human ability in a domain, there are many reasons why AI systems that capture human-like behavior would be desirable: humans may want to learn from them, they may need to collaborate with them, or they may expect them to serve as partners in an extended interaction. Motivated by this goal of human-like AI systems, the problem of predicting human actions — as opposed to predicting optimal actions — has become an increasingly useful task. We extend this… CONTINUE READING

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