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SUMMARY:Mutual Modelling in Human-Robot Interaction
DTSTART:20190626T120000
DTEND:20190626T140000
DTSTAMP:20260407T021247Z
UID:702ab4159a2fb9a05a911ba31b5029bc849f2df4f2f3aee8f59bf6ad
CATEGORIES:Conferences - Seminars
DESCRIPTION:Utku Norman\nEDIC candidacy exam\nExam president: Prof. Aude B
 illard\nThesis advisor: Prof. Pierre Dillenbourg\nCo-examiner: Prof. Fréd
 éric Kaplan\n\nAbstract\nIn the context of collaborative learning with a 
 robot\,\nthe ability to build and maintain a mental model of the other\nis
  essential to comprehend the other and react properly. As\nhumans\, this s
 kill of mutual modeling is performed during most\ninteractions by attribut
 ing goals and beliefs to others. Thus\, we\nconsider how to equip a robot 
 with mutual modelling capabilities\nin order to increase the quality of th
 e dialogue and hopefully\nthe learning gains. As background\, we present t
 hree papers\non i) methodologies for an agent to model another agent\, ii)
  a\nBayesian framework for accounting how humans model an agent\,\nand iii
 ) a study on grounding\, i.e. the process of constructing a\nmutual unders
 tanding\, in collaborative problem solving.\n\nBackground papers\nAutonomo
 us agents modelling other agents: A comprehensive survey and open problems
 . Artificial Intelligence\, 258 (May 2018)\, 66–95. by Albrecht\, S. V.\
 , & Stone\, P.\nRational quantitative attribution of beliefs\, desires and
  percepts in human mentalizing\, by  Baker\, C. L.\, Jara-Ettinger\, J.\,
  Saxe\, R.\, & Tenenbaum\, J. B. Nature Human Behaviour\, 1(4)\, 1–10.\n
 Sharing Solutions: Persistence and Grounding in Multimodal Collaborative P
 roblem Solving\, by  Dillenbourg\, P.\, & Traum\, D. (2006). Journal of t
 he Learning Sciences\, 15(1)\, 121–151.\n 
LOCATION:RLC D1 661 https://plan.epfl.ch/?room==RLC%20D1%20661
STATUS:CONFIRMED
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