TY - GEN
T1 - A Bounded Rationality Account of Wishful Thinking
AU - Neumann, Rebecca
AU - Rafferty, Anna N.
AU - Griffiths, Thomas L.
N1 - Publisher Copyright:
© 2014 Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014. All rights reserved.
PY - 2014
Y1 - 2014
N2 - People tend towards wishful thinking, in which they overestimate the probability of favorable outcomes and underestimate the probability of unfavorable outcomes. Many explanations for this phenomenon focus on its irrationality. We explore whether wishful thinking could actually help people make better decisions given that they have limited cognitive resources. We consider a situation in which multiple decisions must be made over a period of time, where the consequences of these decisions are not fully determined. We model this situation as a Markov decision process, and incorporate limited cognitive resources by varying the amount of time in the future that the agent considers the consequences of its decisions. Through simulations, we show that with limited cognitive resources, this model can exhibit better performance by incorporating a bias towards wishful thinking. This advantage occurs across a range of decision-making environments, suggesting that the same effect could be applicable to many real life scenarios.
AB - People tend towards wishful thinking, in which they overestimate the probability of favorable outcomes and underestimate the probability of unfavorable outcomes. Many explanations for this phenomenon focus on its irrationality. We explore whether wishful thinking could actually help people make better decisions given that they have limited cognitive resources. We consider a situation in which multiple decisions must be made over a period of time, where the consequences of these decisions are not fully determined. We model this situation as a Markov decision process, and incorporate limited cognitive resources by varying the amount of time in the future that the agent considers the consequences of its decisions. Through simulations, we show that with limited cognitive resources, this model can exhibit better performance by incorporating a bias towards wishful thinking. This advantage occurs across a range of decision-making environments, suggesting that the same effect could be applicable to many real life scenarios.
KW - Markov decision processes
KW - rational process models
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M3 - Conference contribution
AN - SCOPUS:84994557997
T3 - Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
SP - 1210
EP - 1215
BT - Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PB - The Cognitive Science Society
T2 - 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Y2 - 23 July 2014 through 26 July 2014
ER -