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ICCBR
2007
Springer
13 years 11 months ago
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
Thomas Gabel, Martin Riedmiller
ICRA
2009
IEEE
259views Robotics» more  ICRA 2009»
13 years 11 months ago
Constructing action set from basis functions for reinforcement learning of robot control
Abstract— Continuous action sets are used in many reinforcement learning (RL) applications in robot control since the control input is continuous. However, discrete action sets a...
Akihiko Yamaguchi, Jun Takamatsu, Tsukasa Ogasawar...
ATAL
2010
Springer
13 years 6 months ago
Basis function construction for hierarchical reinforcement learning
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...
Sarah Osentoski, Sridhar Mahadevan
ICMLA
2008
13 years 6 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux
SMI
2003
IEEE
223views Image Analysis» more  SMI 2003»
13 years 10 months ago
Skeleton Extraction of 3D Objects with Radial Basis Functions
Skeleton is a lower dimensional shape description of an object. The requirements of a skeleton differ with applications. For example, object recognition requires skeletons with pr...
Wan-Chun Ma, Fu-Che Wu, Ming Ouhyoung