Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach

Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach (2003)

by Christopher G. Atkeson , Jun Morimoto

Venue:	In NIPS 15
Citations:	23 - 3 self

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Datum	Value	Source
TITLE	Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach	user correction - Legacy Corrections
AUTHOR NAME	Christopher G. Atkeson	user correction - Legacy Corrections
AUTHOR AFFIL	; Robotics Institute and HCII; Carnegie Mellon University; ATR Human Information Science Laboratories, Dept. 3	user correction - Legacy Corrections
AUTHOR ADDR	; Pittsburgh, PA 15213, USA; Keihanna Science City; Kyoto 619-0288, Japan	user correction - Legacy Corrections
AUTHOR NAME	Jun Morimoto	user correction - Legacy Corrections
ABSTRACT	A longstanding goal of reinforcement learning is to develop nonparametric representations of policies and value functions that support rapid learning without suffering from interference or the curse of dimensionality.	user correction - Legacy Corrections
YEAR	2003	INFERENCE
VENUE	In NIPS 15	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	1611--1618	INFERENCE
VOLUME	15	INFERENCE
CITATIONS	15 found	ParsCit 1.0