Gadaleta Sabino, Dangelmayr Gerhard
Colorado State University, Department of Mathematics, Engineering E121, Ft. Collins, Colorado 80523.
Chaos. 1999 Sep;9(3):775-788. doi: 10.1063/1.166451.
A general purpose chaos control algorithm based on reinforcement learning is introduced and applied to the stabilization of unstable periodic orbits in various chaotic systems and to the targeting problem. The algorithm does not require any information about the dynamical system nor about the location of periodic orbits. Numerical tests demonstrate good and fast performance under noisy and nonstationary conditions. (c) 1999 American Institute of Physics.
介绍了一种基于强化学习的通用混沌控制算法，并将其应用于各种混沌系统中不稳定周期轨道的稳定化以及目标问题。该算法不需要任何关于动力学系统或周期轨道位置的信息。数值测试表明，在噪声和非平稳条件下，该算法具有良好且快速的性能。（c）1999美国物理研究所。
