Synchronous online learning for zero-sum two-player games and H-infinity control
Draguna Vrabie, Kyriakos G. Vamvoudakis, Frank L. Lewis · Institution of Engineering and Technology eBooks · 2012
In this chapter, methods for online gaming are provided for the online solution of two-player zero-sum infinite-horizon games, through learning the saddle-point strategies in real time. The dynamics may be nonlinear in continuous time and are assumed known in this chapter. A novel neural-network (NN) adaptive control technique is given here that is based on reinforcement learning techniques, whereby the control and disturbance policies are tuned online using data generated in real time along the system trajectories.