“Self-Deceptive Decision Making Normative and Descriptive Insights” by Jonathan Y. Ito, David V. Pynadath, and Stacy C. Marsella. In Proceedings of the Conference on Autonomous Agents and Multiagent Systems AAMAS, May 2009.
Computational modeling of human belief maintenance and decision-making processes has become increasingly important for a wide range of applications. We present a framework for modeling the psychological phenomenon of self-deception in a decision-theoretic framework. Specifically, we model the self-deceptive behavior of wishful thinking as a psychological bias towards the belief in a particularly desirable situation or state. By leveraging the structures and axioms of expected utility (EU) we are able to operationalize both the determination and the application of the desired belief state with respect to the decision-making process of expected utility maximization. While we categorize our framework as a descriptive model of human decision making, we show that when specific errors are present, the realized expected utility of an action biased by wishful thinking can exceed that of an action motivated purely by the maximization of expected utility. Finally, in order to provide a descriptive characterization of our framework, we present a discussion of wishful thinking with respect to the Certainty Effect and the Allais Paradox, two specific documented inconsistencies of human behavior. In this discussion we show that our framework has the descriptive flexibility needed to account for both the Certainty Effect and Allais Paradoxes.
BibTeX entry:
@inproceedings{ItoAAMAS09,
author = {Jonathan Y. Ito and David V. Pynadath and Stacy C. Marsella},
title = {Self-Deceptive Decision Making Normative and Descriptive Insights},
booktitle = {Proceedings of the Conference on Autonomous Agents and
Multiagent Systems {AAMAS}},
pages = {},
month = may,
year = {2009},
url = {https://stacymarsella.org/publications/pdf/ItoAAMAS09.pdf}
}
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