Self-Deceptive Decision Making: Normative and Descriptive Insights

Abstract

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) Theory 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 in certain circumstances the realized expected utility of an action biased by wishful thinking can exceed that of an action motivated purely by the maximization of perceived expected utility. Finally, we show that our framework of self-deception and wishful thinking has the descriptive flexibility to account for the inconsistencies highlighted by the Common Ratio Effect and the Allais Paradox.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
AD1171475

Entities

People

  • David V. Pynadath
  • Jonathan Y. Ito
  • Stacy C. Marsella

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Application Software
  • Artificial Intelligence
  • Autonomous Agents
  • Behavioral Sciences
  • Computational Modeling
  • Deception
  • Environment
  • Human Behavior
  • Human Emotions
  • Multiagent Systems
  • Neurobehavioral Manifestations
  • New York
  • Operations Research
  • Probability
  • Probability Distributions
  • Psychology
  • Reasoning
  • Resilience
  • Social Psychology
  • Standards
  • Thinking
  • Uncertainty

Readers

  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.