Close
This site uses cookies

By using this site, you consent to our use of cookies. You can view our terms and conditions for more information.

A general architecture for modeling the dynamics of goal-directed motivation and decision making

Authors
Dr. Timothy Ballard
The University of Queensland ~ School of Psychology
Andrew Neal
The University of Queensland
Simon Farrell
University of Western Australia ~ School of Psychological Science
Prof. Andrew Heathcote
Univeristy of Amsterdam ~ Psychology
Abstract

We present a unified model of the spatial and temporal dynamics of motivation during goal pursuit. We use the model to integrate and compare six theoretical perspectives that make different predictions about how motivation changes as a person comes closer to achieving a goal, as a deadline looms, and as a function of whether the goal is being approached or avoided. We fit the model to data from three experiments that examine how these factors combine to produce changes in motivation over time. We show that motivation changes in a complex manner that cannot be accounted for by any one previous theoretical perspective, but that is well-characterized by our unified model. Our findings highlight the importance of theoretical integration when attempting to understand the factors driving motivation and decision making in the context of goal pursuit.

Tags

Keywords

motivation
goal pursuit
decision making
Bayesian modeling
approach/avoidance

Topics

Cognitive Modeling
Decision Making
Bayesian Modeling
Theory development
Discussion
New

Interesting stuff! It seems to me like most motivational functions are not linear but in fact have some kind of a parabolic shape, with the highest motivation somewhere in the middle distance: you are not so close to the goal that you feel you're done, and you're not so far away you feel it's irrelevant. Have you considered such a function? And yo...

Dr. Marieke Van Vugt 0 comments

Thank you very much for your interesting talk! I would like to ask you about the motivational value of a goal (M) which is the weighted sum of the three gradient perspectives. Does this implementation of the architecture imply that, in each trial, all three perspectives are (proportionally) taken into account? and if yes, I am wondering whether a m...

Dimitris Katsimpokis 0 comments

I would be interested to hear more about how you plan to integrate this work with LBA, as you mention at the end of the talk. Would this be across trials, perhaps working toward achieving N trials correct in under a minute, and then observing how the individual-level motivational gradients pull the LBA parameters? Very interested to hear (in the ...

Dr. Beth Baribault 0 comments
individual differences Last updated 4 years ago

thank you for the very interesting talk I really enjoyed the intro, it is quite remarkable how cognitive psychology has managed to produce so many theories, covering the whole range of possible scenarios! I wondered if the individual differences you highlight are stable and if they could link in any way with personality differences in terms of im...

Dr. Aline Bompas 0 comments

you have a very interesting model, and nice experiments to support it we followed up our earlier Townsend & Busemeyer(1989) paper that you cite with this little known work, but it is closely related to your model Busemeyer, J. R., Townsend, J. T., & Stout, J. C. (2002) Motivational Underpinnings of Utility in Decision Making: Decision Fie...

Dr. Jerome Busemeyer 0 comments
Cite this as:

Ballard, T., Neal, A., Farrell, S., & Heathcote, A. (2020, July). A general architecture for modeling the dynamics of goal-directed motivation and decision making. Paper presented at Virtual MathPsych/ICCM 2020. Via mathpsych.org/presentation/34.