Contemplation vs. Intuition: A Reinforcement Learning Perspective

Speaker
Anna Rubinchik
Date
22/03/2016 - 12:30 - 11:00Add To Calendar 2016-03-22 11:00:00 2016-03-22 12:30:00 Contemplation vs. Intuition: A Reinforcement Learning Perspective Abstract: In a search for a positive model of decision-making with observable primitives, we rely on the burgeoning literature in cognitive neuroscience to construct a three-element machine (agent). Its control unit initiates either impulsive or cognitive element to solve a problem in a stationary Markov environment, the element “chosen” depends on whether the problem is mundane or novel, memory of past successes and the strength of inhibition. Our predictions are based on a stationary asymptotic distribution of the memory, which, depending on the parameters, can generate different “characters”, e.g., an uptight dimwit, who could succeed more often with less inhibition, as well as a relaxed wiseguy, who could gain more with a stronger inhibition of impulsive (intuitive) responses. As one would expect, stronger inhibition and lower cognitive costs increase the frequency of decisions made by the cognitive element. More surprisingly, increasing the “carrot” and reducing the “stick” (being in a more supportive environment) enhances contemplative decisions (made by the cognitive unit) for an alert agent, i.e., the one who identifies novel problems frequently enough. Economics building (No. 504), room 011 אוניברסיטת בר-אילן - Department of Economics Economics.Dept@mail.biu.ac.il Asia/Jerusalem public
Place
Economics building (No. 504), room 011
Affiliation
Haifa University
Abstract

Abstract: In a search for a positive model of decision-making with observable primitives, we rely on the burgeoning literature in cognitive neuroscience to construct a three-element machine (agent). Its control unit initiates either impulsive or cognitive element to solve a problem in a stationary Markov environment, the element “chosen” depends on whether the problem is mundane or novel, memory of past successes and the strength of inhibition.
Our predictions are based on a stationary asymptotic distribution of the memory, which, depending on the parameters, can generate different “characters”, e.g., an uptight dimwit, who could succeed more often with less inhibition, as well as a relaxed wiseguy, who could gain more with a stronger inhibition of impulsive (intuitive) responses.
As one would expect, stronger inhibition and lower cognitive costs increase the frequency of decisions made by the cognitive element. More surprisingly, increasing the “carrot” and reducing the “stick” (being in a more supportive environment) enhances contemplative decisions (made by the cognitive unit) for an alert agent, i.e., the one who identifies novel problems frequently enough.

Attached file

Last Updated Date : 03/01/2016