Career: Applications Of Bayesian Inference To Human Memory And Decision-Making

Description

The objective of this research is to examine how an individual's experiences influence his or her beliefs and how these, in turn, impact intertemporal decisions. Understanding how experiences and resulting beliefs impact future choice contributes to the national health through application to questions of medication adherence and health outcomes (e.g., how patient' uncertainty about illnesses might affect adherence choices.) The project also contributes to national prosperity and welfare through the provision of integrated in-class and laboratory training of graduate students and undergraduates in advanced programming and Bayesian Cognitive Modeling. The research program also seeks to advance diversity in STEM fields through outreach focused on attracting women and underrepresented groups to the academic setting, and continued post-degree mentoring, e.g., outreach to pre-college organizations serving underrepresented minorities and organizations promoting retention of women in science.Our beliefs about the regularities of our environment shape our understanding of the world, and in turn, influence our cognitive processes and behavior. Beliefs are important not only for recalling the past and making decisions in the now, but also for making predictions about the future. People develop well-calibrated beliefs based on their life experiences. However, subjective experiences leading to individual differences in beliefs have also been found to bias decision processes. Time preference (placing greater value on earlier outcomes by discounting the utility of later outcomes) is one example where human choice and behavior is influenced by strong individual differences, as well as changes within the individual. While Discounted Utility, the accepted model of normative intertemporal choice, assumes consistent assignment of discounting rates in time preference (i.e., stable individual difference), it has been suggested that people might exhibit a change in time preference due to beliefs about the uncertainty in the environment. An important question that remains unexplored is: what is the effect of changes in the environment on subjective beliefs and the influence of changing beliefs on memory and decision making under uncertainty (e.g., predictions for the future). This research provides a new framework for inferring individual differences via the integrated application of Bayesian analysis to Bayesian models of cognition. This integrative approach makes it possible to infer individual differences in the underlying parameters of the Bayesian cognitive model, and can be used to address how changing beliefs influence how and what we remember, and the value of future outcomes. The theory driven goal is to challenge the assumption of a constant discounting rate, and instead assume that the rate changes, but that the system for determining the rate remains consistent. The integrative approach makes it possible to implement and compare multiple competing cognitive models of the effect of individual discounting rates on time preference.
StatusActive
Effective start/end date7/1/156/30/20

Funding

  • National Science Foundation (NSF)

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Bayesian inference
Decision making
Individual differences
Time preference
Discounting
Integrated
Prediction
Uncertainty
Adherence
Outreach
Health
Placing
Cognitive processes
Health outcomes
Cognitive modeling
Mentoring
Cognition
Bayesian analysis
Minorities
Regularity