People are better at maximizing expected gain in a manual aiming task with rapidly changing probabilities than with rapidly changing payoffs.

@article{Neyedli2014PeopleAB,
  title={People are better at maximizing expected gain in a manual aiming task with rapidly changing probabilities than with rapidly changing payoffs.},
  author={Heather F. Neyedli and Timothy N. Welsh},
  journal={Journal of neurophysiology},
  year={2014},
  volume={111 5},
  pages={
          1016-26
        }
}
Previous research has shown that humans can select movements that achieve their goals, while avoiding negative outcomes, by selecting an "optimal movement endpoint." This optimal endpoint is modeled based on the participants' endpoint variability and the payoffs associated with the target and penalty regions within the environment. Although the values associated with our goals vary on a moment-to-moment basis in our daily interactions, the adaptation of endpoint selection to changing payoffs in… CONTINUE READING
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