An Evolutionary Game Model of Self-Deception and the Effect of Belief on Performance
Open Access
- Author:
- Achampong, Christina
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- None
- Committee Members:
- Eli Christopher C Byrne, Thesis Advisor/Co-Advisor
Soundar Kumara, Thesis Advisor/Co-Advisor
Dr Christopher C Byrne, Thesis Advisor/Co-Advisor - Keywords:
- collaboration
competition
hawk-dove
evolutionary dynamics
game theory
self-deception - Abstract:
- Self-deception at first thought may appear to be counterintuitive as it pertains to evolutionary strategies. It would seem that in order to best adapt, it is first necessary to make an accurate assessment of one’s state. Yet, phenomena such as the placebo effect continue to suggest that there is some benefit to self-deception when it comes in the form of optimistic belief. In previous work, Byrne and Kurland demonstrated that self-deception could be fitness enhancing if it enables one to better deceive an opponent into not competing for a resource. However, their model did not consider any effect of self-deception on one’s actual performance if the opponent competes. This thesis is a natural extension of Byrne and Kurland’s work. In this work, the relationship between beliefs and performance in fitness competition is examined. The present work first assumes that belief in victory enhances one’s performance and subsequently one’s probability of victory. It further assumes that one’s capacity to believe in victory can be limited by past experiences of defeat. Based on these assumptions, an evolutionary game model is used to analyze the relationship between a player’s belief in victory and the final outcome of a competitive encounter. Simulation is employed to provide a bridge between Byrne & Kurland’s prior work based on probability distributions and future studies in which discrete player histories must be tracked. The first step is to study a model where belief in victory enhances performance. Next, the trends of a model where belief does not affect performance are examined. The evolutionarily stable strategies resulting from the simulation runs are presented and interpreted. Comparing the two models, conclusions are made about the relationship between beliefs and performance.