An Adaptive Approach to Human Decision Making : Learning Theory , Decision Theory , and Human Performance

@inproceedings{Busemeyer2004AnAA,
  title={An Adaptive Approach to Human Decision Making : Learning Theory , Decision Theory , and Human Performance},
  author={Jerome R. Busemeyer and In Jae Myung},
  year={2004}
}
This article describes a general model of decision rule learning, the rule competition model, composed of 2 parts: an adaptive network model that describes how individuals learn to predict the payoffs produced by applying each decision rule for any given situation and a hill-climbing model that describes how individuals learn to fine tune each rule by adjusting its parameters. The model was tested and compared with other models in 3 experiments on probabilistic categorization. The first… CONTINUE READING

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