Name
Abstract | ||
|---|---|---|
Traditional evolutionary game theory describes how certain strategy spreads throughout the system where individual player imitates the most successful strategy among its neighborhood. Accordingly, player doesnu0027t have own authority to change their state. However in the human society, peoples do not just follow strategies of other people, they choose their own strategy. In order to see the decision of each agent in timely basis and differentiate between network structures, we conducted multi-agent based modeling and simulation. In this paper, agent can decide its own strategy by payoff comparison and we name this agent as Self-motivated agent. To explain the behavior of self-motivated agent, prisoneru0027s dilemma game with cooperator, defector, loner and punisher are considered as an illustrative example. We performed simulation by differentiating participation rate, mutation rate and the degree of network, and found the special coexisting conditions. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Multiagent Systems | Strategy,Computer science,Modeling and simulation,Simulation,Loner,Complex network,Artificial intelligence,Dilemma,Evolutionary game theory,Management science,Stochastic game,Network structure |
DocType | Volume | Citations |
Journal | abs/1604.03747 | 0 |
PageRank | References | Authors |
0.34 | 2 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sundong Kim | 1 | 0 | 1.01 |
| Jae-Jin Lee | 2 | 27 | 8.69 |