Kernelized Value Function Approximation for Reinforcement Learning Gavin Taylor Ronald Parr Department of Computer Science, Duke University, Durham, NC[removed]USA

First Page		Document Content
Date: 2009-04-22 16:59:18 Normal distribution Singular value decomposition Least squares Reinforcement learning Gaussian process Proto-value functions Markov decision process Gaussian function Regularization Statistics Mathematics Regression analysis		Kernelized Value Function Approximation for Reinforcement Learning Gavin Taylor Ronald Parr Department of Computer Science, Duke University, Durham, NC[removed]USA Add to Reading List Source URL: www.cs.duke.edu Download Document from Source Website File Size: 949,58 KB Share Document on Facebook

	Value Function Approximation in Reinforcement Learning using the Fourier Basis George Konidaris1,3 1 MIT CSAIL DocID: 1r3Y6 - View Document
	Evolutionary Feature Evaluation for Online Reinforcement Learning DocID: 1qvrS - View Document
	Analyzing Feature Generation for Value-Function Approximation Ronald Parr Christopher Painter-Wakefield Department of Computer Science, Duke University, Durham, NC[removed]USA Lihong Li DocID: ZOKm - View Document
	Kernelized Value Function Approximation for Reinforcement Learning Gavin Taylor Ronald Parr Department of Computer Science, Duke University, Durham, NC[removed]USA DocID: ZNH2 - View Document
	An Analysis of Linear Models, Linear Value-Function Approximation, and Feature Selection for Reinforcement Learning Ronald Parr? Lihong Li† Gavin Taylor? Christopher Painter-Wakefield? DocID: ZzY6 - View Document