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UID:34003@https://evenements.uqam.ca
DTSTART:20260519T093000Z
SEQUENCE:4
TRANSP:OPAQUE
URL:https://evenements.uqam.ca/evenements/soutenance-de-matthew-martin-doct
 orat-en-informatique-cognitive-cognitive-and-computational-tools-to-improv
 e-reasoning-and-decision-making-in-the-intelligence-community/34003?date=2
 026-05-19_09-30-00
LOCATION:UQAM - Pavillon Président-Kennedy (PK) (201\, avenue du Présiden
 t-Kennedy\, Montréal )
SUMMARY:Soutenance de Matthew Martin\, doctorat en informatique cognitive: 
 «Cognitive and computational tools to improve reasoning and decision maki
 ng in the intelligence community»
CLASS:PUBLIC
DESCRIPTION:SOUTENANCE DE THÈSE   \n\n\n \n\n\nVous êtes cordialement
  invités!   \n\n\n \n\n\nMardi 19 mai 2026 \n\n\n9h30\n\n\nLocal: PK
 -2265  \n\n\n \n\n\nTITRE : Cognitive and computational tools to impr
 ove reasoning and decision making in the intelligence community\n\n\n \n\
 n\nPrésenté par\n\n\nMatthew MARTIN\, personne doctorante en informatiqu
 e cognitive  \n\n\n \n\n\nRÉSUMÉ\n\n\nImproving reasoning and decisio
 n-making in the intelligence community (IC) could reduce the chance of war
 s and other catastrophes.  This thesis describes three projects that deve
 lop and test cognitive and computional tools to improve reasoning and deci
 sion-making.  The first project conducted a content analysis of intellige
 nce products to examine the relationships between techniques used\, adhere
 nce to IC of Standardizing Probability Ranges and Timeline were predictive
  of IC norm adherence.  In the second project\, two experiments used the 
 Practical scoring rule as performance feedback to train better calibration
  of confidence.  The results showed no improvement to calibration from tr
 aining\, contrary to previous results.  However\, actively open-minded th
 inking was positively related to overall calibration.  The third project 
 usec recalibration and weighted aggregation in combination with Bayesian n
 etworks (BNs) and logistic regression to improve the accuracy of probabili
 stic forecasts made during a multi-year forecasting tournament.  Recalibr
 ation and aggregation alone produces the most accurate forecasts\, followe
 d by BNs\, then logistic regression.  Future studies should use content a
 nalysis on a larger set of real intelligence products to address questions
  of external validity ans increase the power of the first project.  For t
 he second project\, the effects of participant motivation and comprehensio
 n should be probed to determine when calibration training with the Practic
 al score is effective.  Finally\, for the third project\, more advanced m
 achine learning techniques like hierarchical BNs and ensemble methods shou
 ld be expoored to further increase the accuracy of recalibrated aggregated
  forecasts.\n\n\n \n\n\nMots clés : Reasoning\, decision-making\, intell
 igence community\, probability\, forecasting\, content analysis\, calibrat
 ion\, machine learning\, Bayesian networks\, logistic regression\n\n\n \n
 \n\n JURY D'ÉVALUATION\n\n\nMandeep Dhami\, Université Middlesex de Lon
 dres\, professeure au département de psychologie (membre externe)\n\n\nJa
 nie Brisson\, UQAM\, professeure au département d'éducation et pédagogi
 e (membre interne) \n\n\nHakim Lounis\, UQAM\, professeur au département
  d'informatique (membre interne et président du jury)\n\n\nSerge Robert\,
  UQAM\, professeur au de philosophie (direction de recherche)  \n\n\nRog
 er Villemaire\, UQAM\, professeur au département d'informatique (codirect
 ion de recherche)\n\n\n \n\nMot-clés : IA \; intelligence artificielle\,
  société\, Soutenance de thèse\, LATECE\, LATECE UQAM INFORMATIQUE\, In
 stitut des sciences cognitives\, ISC\, CRIA\, doctorat en informatique\, d
 octorat en informatique cognitive\, département de philosophie\, Départe
 ment d'informatique\, régression logistique\, réseaux bayésiens\, appre
 ntissage automatique\, analyse de contenu\, Probabilités\, intelligence c
 ommunity\, communauté du renseignement\, prise de décision\, raisonnemen
 t\n\nPrix : Gratuit\n\n
CATEGORIES:Présentation,Thèse
DTSTAMP:20260513T142734Z
CREATED:20260505T133451Z
LAST-MODIFIED:20260506T113900Z
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