Choice engineering and the modeling of operant learning
Wednesday, April 7, 2021
05:00 UTC
Yonatan Loewenstein
The Hebrew University
Recording
Open recording
Hosted by van Vreeswijk TNS70 minutes
Abstract
Organisms modify their behavior in response to its consequences, a phenomenon referred to as operant learning. Contemporary modeling of this learning behavior is based on reinforcement learning algorithms. I will discuss some of the challenges that these models face, and proposed a new approach to model-selection that is based on testing their ability to engineer behavior. Finally, I will present the results of The Choice Engineering Competition – an academic competition that compared the efficacies of qualitative and quantitative models of operant learning in shaping behavior.
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