Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL), for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares...

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Bibliographic Details
Main Authors: Bo Liu, Sanfeng Chen, Shuai Li, Yongsheng Liang
Format: Article
Language:English
Published: MDPI AG 2012-02-01
Series:Sensors
Subjects:
Markov Decision Process
sensor-actuator systems
random Projections
Kernelized Least Square Policy Iteration
Online Access:http://www.mdpi.com/1424-8220/12/3/2632/

Internet

http://www.mdpi.com/1424-8220/12/3/2632/

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