Multi-agent differential graphical games

By Kyriakos G. Vamvoudakis, Frank L. Lewis, Gregory R. Hudas. Proceedings of the 30th Chinese Control Conference, 2011

335 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/23854806a706f343904c56e5f6ceea4e043b33df

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. He Jiang
2. Geyang Xiao
3. Yanhong Luo
4. Huaguang Zhang
5. Guanghong Yang
6. Guoqiang Hu
7. Maojiao Ye
8. Derong Liu

In Computer Networks and Communications

1. Maojiao Ye
2. Guoqiang Hu
3. Guanghong Yang
4. Hongjing Liang
5. Tao Feng
6. Huaguang Zhang
7. Yanhong Luo
8. Chao Deng

Citations in the corpus

• Distributed Nash Equilibrium Seeking by a Consensus Based Approach (2016, methodology): “, [5] and [7]–[9]), this paper addresses Nash equilibrium seeking under local communication network, i.”
• Data-Driven Optimal Consensus Control for Discrete-Time Multi-Agent Systems With Unknown Dynamics Using Reinforcement Learning Method (2017, methodology): “Following the idea of the previous work in [38], [40], and [42], the local performance indices, also called local cost functions, are defined as follows:”
• Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach (2015, background): “The distributed games on graphs were studied by introducing the notion of iterative Nash equilibrium in [29], where each agent only minimizes its own performance index.”