Name
Abstract | ||
|---|---|---|
Multiagent systems (MASs) are usually applied with agents classified into leaders and followers, where selecting appropriate leaders is an important issue for formation control applications. In this paper, we investigate two leader selection problems in second-order MAS, namely, the problem of choosing up to a given number of leaders to minimize the formation error and the problem of choosing the minimum number of leaders to achieve a tolerated level of error. We propose a game theoretical method to address them. Specifically, we design a supermodular game for the leader selection problems and theoretically prove its supermodularity. In order to reach Nash equilibrium of the game, we propose strategies for the agents to learn to select leaders based on stochastic fictitious play. Extensive simulation results demonstrate that our method outperforms existing ones. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TNNLS.2019.2900592 | IEEE transactions on neural networks and learning systems |
Keywords | Field | DocType |
Games,Nash equilibrium,Nickel,Multi-agent systems,Control systems,Shape | Computer science,Multi-agent system,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
30 | 12 | 2162-237X |
Citations | PageRank | References |
0 | 0.34 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Xue | 1 | 103 | 16.03 |
| Xianghui Cao | 2 | 555 | 43.42 |