Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Ultimatum Game Model Based on Facial Trait Inference

Authors
Yujia Wu
Corresponding Author
Yujia Wu
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.16How to use a DOI?
Keywords
Ultimatum game; Trait inference; FS model.
Abstract

The existence of a beauty premium in the labor market suggests that appearance can exert effect in the real world. We explored facial trait inference-especially focused on facial attractiveness and facial trustworthiness-in an Ultimatum Game experiment, which is commonly used to examine economic decision making [1]. Based on the traditional FS model, which clearly described the function of ultimatum game, we modified and made improvements of it and constructed a model that was appropriate for our research. These findings point to important effects of facial trait inferences on decision and provide initial insight into the psychological processes regarding to the decision behavior.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.16How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yujia Wu
PY  - 2016/11
DA  - 2016/11
TI  - Ultimatum Game Model Based on Facial Trait Inference
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 87
EP  - 90
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.16
DO  - https://doi.org/10.2991/aiea-16.2016.16
ID  - Wu2016/11
ER  -