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ICML
2005
IEEE
14 years 11 months ago
New approaches to support vector ordinal regression
In this paper, we propose two new support vector approaches for ordinal regression, which optimize multiple thresholds to define parallel discriminant hyperplanes for the ordinal ...
Wei Chu, S. Sathiya Keerthi
GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
14 years 2 months ago
Reinforcement learning for games: failures and successes
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
Wolfgang Konen, Thomas Bartz-Beielstein
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
13 years 8 months ago
Reinforcement learning of motor skills in high dimensions: A path integral approach
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
SAB
2010
Springer
187views Optimization» more  SAB 2010»
13 years 8 months ago
Learning Robot-Environment Interaction Using Echo State Networks
Learning robot-environment interaction with echo state networks (ESNs) is presented in this paper. ESNs are asked to bootstrap a robot’s control policy from human teacher’s dem...
Mohamed Oubbati, Bahram Kord, Günther Palm
ICRA
2002
IEEE
105views Robotics» more  ICRA 2002»
14 years 3 months ago
Learning Behavioral Parameterization using Spatio-Temporal Case-Based Reasoning
This paper presents an approach to learning an optimal behavioral parameterization in the framework of a Case-Based Reasoning methodology for autonomous navigation tasks. It is ba...
Maxim Likhachev, Michael Kaess, Ronald C. Arkin