A reinforcement learning-based scheme for direct adaptive optimal control of linear stochastic systems

作者：Wong Wee Chin; Lee Jay H^*

来源：Optimal Control Applications and Methods, 2010, 31(4): 365-374.

DOI：10.1002/oca.915

• reinforcement learning
• linear systems
• stochastic adaptive optimal control

Reinforcement learning where decision-making agents learn optimal policies through environmental interactions is an attractive paradigm for model-free, adaptive controller design. However, results for systems with continuous state and action variables are rare. In this paper, we present convergence results for optimal linear quadratic control of discrete-time linear stochastic systems. This work can be viewed as a generalization of a previous work on deterministic linear systems. Key differences between the algorithms for deterministic and stochastic systems are highlighted through examples.

• 出版日期2010-8