Do you want BuboFlash to help you learning these things? Or do you want to add or correct something? Click here to log in or create user.

#bayesianism #cognitive-science #computation #computational-psychology
Proba- bilistic models highlight the role of prior knowledge in accounting for how people learn as much as they do from limited ob- served data and provide a framework for ex- plaining precisely how prior knowledge in- teracts with data in guiding generalization and action. They also provide a tool for ex- ploring the kinds of knowledge that people bring to learning and reasoning tasks, allow- ing us to work forwards from rational analy- ses of tasks and environments to predictions about behavior and to work backwards from subjects’ observed behavior to viable as- sumptions about the knowledge they could bring to the task. Crucially, these models do not require that the prior knowledge be innate. Bayesian inference in hierarchi- cal probabilistic models can explain how ab- stract prior knowledge may itself be learned from data and then put to use to guide learn- ing in subsequent tasks and new environ- ments.
If you want to change selection, open document below and click on "Move attachment"


owner: rappatoni - (no access) - [Ron_Sun]_The_Cambridge_Handbook_of_Computational.pdf, p77


statusnot read reprioritisations
last reprioritisation on suggested re-reading day
started reading on finished reading on



Do you want to join discussion? Click here to log in or create user.