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IJCAI
2007
14 years 11 months ago
Utile Distinctions for Relational Reinforcement Learning
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
William Dabney, Amy McGovern
ICML
2004
IEEE
15 years 10 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ICRA
2009
IEEE
259views Robotics» more  ICRA 2009»
15 years 4 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...
IROS
2009
IEEE
154views Robotics» more  IROS 2009»
15 years 4 months ago
Consideration on robotic giant-swing motion generated by reinforcement learning
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
Masayuki Hara, Naoto Kawabe, Naoki Sakai, Jian Hua...
KDD
2010
ACM
282views Data Mining» more  KDD 2010»
15 years 1 months ago
Optimizing debt collections using constrained reinforcement learning
In this paper, we propose and develop a novel approach to the problem of optimally managing the tax, and more generally debt, collections processes at financial institutions. Our...
Naoki Abe, Prem Melville, Cezar Pendus, Chandan K....