Distributed Saddle-Point Seeking via a Continuous-time Multi-Agent System
Additional Document Info
2017 IEEE. This paper presents a continuous-time multi-agent system for seeking constrained saddle-points in a distributed manner. In the system, two groups of agents are employed for computing the two state vectors in a saddle-point, respectively. Each agent seeks for consensus with the agents in the same group, and simultaneously optimizes its local objective functions by competing with the agents in the opposite group. In addition, a projection operator is introduced into the dynamics of each agent for dealing with bounded constraints. It is shown that the proposed system is convergent to a saddle-point of the given convex-concave objective function under connected and undirected communication graph. Finally, numerical simulation results are provided to substantiate the effectiveness of the proposed system.
name of conference
2017 International Workshop on Complex Systems and Networks (IWCSN)