A Fuzzy System Approach for Choosing Public Goods Game Strategies

Authors

Garrison W. Greenwood, Portland State UniversityFollow

Published In

2017 IEEE Conference on Computational Intelligence and Games (CIG)

Document Type

Citation

Publication Date

10-2017

Abstract

Replicator equations are regularly used to predict how strategies evolve in social dilemmas. These predictions are based on comparisons between the fitness of a strategy and the average population fitness. Unfortunately, fitness comparisons alone don't provide much insight into how or why individuals choose to cooperate. To overcome this limitation in replicator equations we developed a zero order Seguno fuzzy system to model individual player decisions in a public goods game. Our simulation results qualitatively match those predicted by the replicator dynamics which validates the approach. This new methodology provides a framework for studying individual decision making in social dilemmas.

Description

©2017 IEEE

Locate the Document

https://doi.org/10.1109/CIG.2017.8080422

DOI

10.1109/CIG.2017.8080422

Persistent Identifier

https://archives.pdx.edu/ds/psu/30638

Citation Details

Greenwood, G. W. (2017, August). A fuzzy system approach for choosing public goods game strategies. In 2017 IEEE Conference on Computational Intelligence and Games (CIG) (pp. 104-109). IEEE.