Name
Abstract | ||
|---|---|---|
Social dilemmas arise whenever individuals must choose between their own self-interests or the welfare of a group. Economic games such as Public Goods Games (PGG) provide a framework for studying human behavior in social dilemmas. Cooperators put their self-interests aside for the group benefit while defectors free ride by putting their self-interests first. Punishment has been shown to be an effective mechanism for countering free riding in both model-based and human PGG experiments. But researchers always assume, since this punishment is costly to the punisher, it must be altruistic. In this study we show costly punishment in a PGG has nothing to do with altruism. Replicator dynamics are used to evolve strategies in a PGG. Our results show even a minority of punishers can improve cooperation levels in a population if the cooperators who punish are trustworthy. Finally, we argue punishment as a strategy in social dilemmas is never altruistic. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/CIG.2018.8490421 | 2018 IEEE Conference on Computational Intelligence and Games (CIG) |
Keywords | Field | DocType |
altruism,costly punishment,public goods games,social dilemma | Population,Altruism,Public good,Sociology,Microeconomics,Replicator equation,Artificial intelligence,Free riding,Welfare,Social dilemma,Aside,Machine learning | Conference |
ISSN | ISBN | Citations |
2325-4270 | 978-1-5386-4360-0 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Garrison W. Greenwood | 1 | 216 | 35.87 |
| Hussein A. Abbass | 2 | 1503 | 144.85 |
| Eleni Petraki | 3 | 19 | 6.20 |