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SUMMARY:Bayesian Brains Without Probabilities - Prof Adam Sanborn\, Univer
 sity of Warwick
DTSTART:20251121T120000Z
DTEND:20251121T133000Z
UID:TALK237175@talks.cam.ac.uk
CONTACT:Psychology Reception
DESCRIPTION:Over the past few decades\, waves of complex probabilistic exp
 lanations have swept through cognitive science\, explaining behaviour as t
 uned to environmental statistics in domains from intuitive physics and cau
 sal learning\, to perception\, motor control and language. Yet people prod
 uce stunningly incorrect answers in response to even the simplest question
 s about probabilities. How can a supposedly rational brain paradoxically r
 eason so poorly with probabilities? Perhaps our minds do not represent or 
 calculate probabilities at all and are\, indeed\, poorly adapted to do so.
  Instead\, the brain could be approximating Bayesian inference through sam
 pling: drawing samples from its distribution of likely hypotheses over tim
 e. Only with infinite samples does a Bayesian sampler conform to the laws 
 of probability\, and in this talk I show how using a finite number of samp
 les systematically generates classic probabilistic reasoning errors in ind
 ividuals\, and how an extended model explains estimates\, choices\, respon
 se times\, and confidence judgments in a variety of tasks.\n\nHost: Dr Deb
 orah Talmi (dt492@cam.ac.uk)\n\nThis talk will be recorded and uploaded to
  the Zangwill Club "Youtube channel":https://www.youtube.com/@zangwillclub
 5226 in due course.
LOCATION:Ground Floor Lecture Theatre\, Department of  Psychology
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