BEGIN:VCALENDAR
VERSION:2.0
PRODID:https://evenements.uqam.ca
X-PUBLISHED-TTL:P1W
BEGIN:VEVENT
UID:32861@https://evenements.uqam.ca
DTSTART:20260305T103000Z
SEQUENCE:6
TRANSP:OPAQUE
URL:https://evenements.uqam.ca/evenements/seminaire-au-dic-human-vs-machine
 -in-the-game-of-hidden-rules-par-javoc-feldman/32861?date=2026-03-05_10-30
 -00
LOCATION:UQAM - Pavillon Président-Kennedy (PK) (201\, avenue du Présiden
 t-Kennedy\, Montréal )
SUMMARY:Séminaire DIC: «Human vs Machine in the Game of Hidden Rules» pa
 r Jacob FELDMAN
CLASS:PUBLIC
DESCRIPTION:Séminaire ayant lieu dans le cadre du doctorat en informatique
  cognitive\, en collaboration avec le centre de recherche CRIA    \n\n
 \n \n\n\nTITRE :  Human vs Machine in the Game of Hidden Rules\n\n\n \
 n\n\nJacob FELDMAN\n\n\nJeudi le 5 mars 2026 à 10h30\n\n\nLocal PK-5115 
 (Il est possible d'y assister en virtuel en vous inscrivant ici)     
           \n\n\n \n\n\nRÉSUMÉ\n\n\nComparisons of human and m
 achine intelligence are often grounded in supposition\, unencumbered by em
 pirical data about human performance. In this talk I'll present results co
 mparing human and machine performance in on a common platform\, the \"Game
  of Hidden Rules\" (GOHR). The GOHR is a simple rule-discovery game in whi
 ch a player---human or AI---tries to classify objects into categories base
 d on an unknown rule that they must infer by trial and error. Human player
 s solve such problems about two orders of magnitude faster than (blank sla
 te) AI models. In general\, human and AI performance are almost completely
  uncorrelated\, suggesting that contemporary AI does not yet effectively r
 eflect the way that humans learn.\n\n\n \n\n\nBIOGRAPHIE\n\n\nJacob FELDM
 AN is Professor of Psychology and Cognitive Science at Rutgers University\
 , where he directs the Visual Cognition Lab. His research focuses on compu
 tational models of human visual perception and concept learning\, particul
 arly perceptual organization\, shape representation\, and categorization. 
 Feldman has worked on the simplicity principle in human concept learning a
 nd Boolean complexity minimization\, as well as on Bayesian models of perc
 eption and learning.\n\n\n \n\n\nRÉFÉRENCES \n\n\nFeldman\, J. (2025).
  Simplicity and complexity of probabilistically-defined concepts. Psycholo
 gical Review\, in press. \n\n\nFeldman\, J. (2024). Probabilistic origins
  of compositional mental representations. Psychological Review\, 131(3)\, 
 599-624. \n\n\nDestler\, N.\, Singh\, M.\, &amp\; Feldman\, J. (2023). Sk
 eleton-based shape similarity. Psychological Review\, 130(6)\, 1653-1671.
  \n\n\nFeldman\, J. (2021). Information-theoretic signal detection theory
 . Psychological Review\, 128(5)\, 976-987.\n\nMot-clés : LLMs\, LATECE UQ
 AM INFORMATIQUE\, LATECE\, CRIA\, Département de Neuroscience\, Sciences 
 cognitives\, Philosophie\, Sciences cognitive\, École de langues\, neuros
 ciences cognitives\, Institut des sciences cognitives\, Apprentissage du l
 angage naturel\, sciences du langage\, apprentissage machine\, apprentissa
 ge automatique\, apprentissage profond\, langage automatique\, langage cog
 nitif\, Cognition humaine\, Cognition\, cognition\, intelligence artificie
 lle\, IA\; intelligence artificielle\; société\, IA\, intelligence artif
 icielle\, IA\, intelligence artificielle\, chatGPT\, enseignement supérie
 ur\, département de linguistique\, Maîtrise en informatique\, maîtrise 
 en psychologie\, doctorat en psychologie\, département de psycho\, dépar
 tement de psychologie\, Département d'informatique\, Faculté des science
 s de l'UQAM\, Faculté des sciences\, doctorat en informatique\, doctorat 
 en informatique cognitive\n\nPrix : Gratuit\n\n
CATEGORIES:Séminaire,Conférence
DTSTAMP:20260912T013348Z
CREATED:20260224T153343Z
LAST-MODIFIED:20260305T125655Z
END:VEVENT
END:VCALENDAR