Corpus ID: 219531217

Implications of Human Irrationality for Reinforcement Learning

@article{Chen2020ImplicationsOH,
  title={Implications of Human Irrationality for Reinforcement Learning},
  author={Haiyang Chen and H. Chang and Andrew Howes},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.04072}
}

Haiyang Chen, H. Chang, Andrew Howes

Published 2020

Computer Science, Mathematics

ArXiv

Recent work in the behavioural sciences has begun to overturn the long-held belief that human decision making is irrational, suboptimal and subject to biases. This turn to the rational suggests that human decision making may be a better source of ideas for constraining how machine learning problems are defined than would otherwise be the case. One promising idea concerns human decision making that is dependent on apparently irrelevant aspects of the choice context. Previous work has shown that… CONTINUE READING

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