Name
Abstract | ||
|---|---|---|
With existence of the social custom or norm, Naylor demonstrates a possibility of stable long-run equilibria of support for a strike in a labor market, and this implies that at least some individuals will behave cooperatively and hence the prisoners' dilemma could be escaped. In this paper, we develop an agent-based simulation system in which artificial adaptive agents have mechanisms of decision making and learning based on neural networks and genetic algorithms, and compare the result of our simulation analysis with that of the mathematical model by Naylor. Especially, while the Naylor model is based on rationality about maximization of individual utility, our agent-based simulation model employs adaptive behavior of agents; agents make decisions by trials and errors and they learn from experiences to make better decisions. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICSMC.2008.4811602 | Singapore |
Keywords | Field | DocType |
decision making,genetic algorithms,multi-agent systems,neural nets,social sciences computing,Naylor mathematical model,agent-based simulation analysis,artificial adaptive agents,decision making,genetic algorithms,labor market,neural networks,prisoners dilemma,social custom,social norms,Multi-agent system,simulation,social norm | Trial and error,Rationality,Agent-based social simulation,Computer science,Prisoner's dilemma,Norm (social),Multi-agent system,Artificial intelligence,Adaptive behavior,Machine learning,Maximization | Conference |
ISSN | ISBN | Citations |
1062-922X E-ISBN : 978-1-4244-2384-2 | 978-1-4244-2384-2 | 1 |
PageRank | References | Authors |
0.38 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ichiro Nishizaki | 1 | 443 | 42.37 |
| Hideki Katagiri | 2 | 436 | 46.48 |
| Toshihisa Oyama | 3 | 1 | 0.38 |
| Tomohiro Hayashida | 4 | 29 | 11.56 |