Center Calendar

Dr. Elizabeth Bonawitz

Tuesday, April 25, 2017, 01:00pm - 02:30pm

Rutgers University-Newark, Department of Psychology

Copy to My Calendar (iCal)

Export Event

Save iCal

Send to Google Calendar

Send to Yahoo Calendar

Send to Outlook Live

Send to Microsoft Outlook

Save iCal

Close

How do children make sense of a causally ambiguous, probabilistic world — rapidly and accurately changing beliefs about it? I will suggest that computational models can provide a precise framework for considering how children should update their beliefs as they encounter new evidence, and they also provide a starting point for considering how ideal learners should interpret ambiguous evidence. Considering how computational models connect to real learners also provides insight into the mechanisms by which child learners approach probabilistic evidence. I will present two projects. The first includes a computational model that takes into account social inferences on the part of the learner and behavioral data from preschoolers that suggest they are sensitive to social information (for better and for worse). In the second half of the talk, I present a simple algorithm for sequentially updating beliefs and show that preschoolers belief updating shows the same signature dependencies of a particular sampling algorithm: win-stay, lose-switch.

Dr. Elizabeth Bonawitz