Abstract
Previous Experiments in the field of human behavior and game theory has shown that loss aversion has a major effect on players’ decisions in coordination problems. The overarching aim of our study was to model the effect of loss aversion on individual player behavior in divergent interest tacit coordination games. Based on a large-scale behavioral data we have designed a model predicting the total number of points players allocate to themselves as a result of increased penalty values in cases of non-coordination. Understanding the effect of loss aversion in case of divergent interest coordination problems on players’ behavior will allow us to better predict the human decision-making process and as a result, create more realistic algorithms for human-machine cooperation’s. Understanding the effect of loss aversion in the context of divergent interest tacit coordination games may enable the construction of better algorithms for human-machine interaction that could more accurately predict human decision behavior under uncertainty.
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