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| Published: August 23, 2020

“What is the significance of feedback and reinforcement learning mechanisms in aiding dynamic decision making?” – proposing a revised hybrid reinforcement learning initiated instance-based model of dynamic decision making

Nilosmita Banerjee

MSc student in Cognitive Computational Neuroscience, Dept. of Psychology, University of Sheffield (United Kingdom) Google Scholar More about the auther

DIP: 18.01.064/20200803

DOI: 10.25215/0803.064

ABSTRACT

Aim: The current study aimed to propose a new hybrid-model called Reinforcement-Learning initiated Instance-based Model which acknowledges the significance of feedback in promoting learning and memory-mechanisms over a period of time to aid Dynamic Decision-Making (DDM), a crucial aspect disregarded by a previous DDM-model called Instance-based Learning Model proposed by Gonzalez et.al.,(2003) as also test this hybrid-model in a novel Financial Expenditure DDM-environment with varying income-periods like income/employment and retirement-phase. Method: In a mixed-measures experimental-design the current study subjected participants (n=48) to a financial DDM-task wherein they undertook discretionary-expenditures during varying income-periods (income-phase/retirement-phase), across two conditions—feedback and no-feedback in two separate decision-making sessions (DMS) 1&2 in each condition. Results: Results indicated that participants in feedback-condition (DMS-1&2) outperformed in the financial DDM-task as compared to those in no-feedback (DMS-1&2) condition. Furthermore, participants in feedback-condition in DMS-1 performed significantly better in DMS-2 without explicit-feedback, while those in no-feedback condition in DMS-1 deteriorated in DMS-2 in DDM-task without feedback, suggesting that feedback facilitated development of memory-instances during the learning-process in DMS-1 which aided DDM in similar DDM-environment (DMS-2). Conclusion: The current study highlighted the significance of feedback in aiding learning and memory-mechanisms in DDM-settings.

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Nilosmita Banerjee @ nbanerjee1@sheffield.ac.uk

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Article Overview

ISSN 2348-5396

ISSN 2349-3429

18.01.064/20200803

10.25215/0803.064

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Published in   Volume 08, Issue 3, July-September, 2020