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AR
2004
84views more  AR 2004»
15 years 3 months ago
Reinforcement learning of humanoid rhythmic walking parameters based on visual information
This paper presents a method for learning the parameters of rhythmic walking to generate purposive humanoid motions. The controller consists of the two layers: rhythmic walking is...
Masaki Ogino, Yutaka Katoh, Masahiro Aono, Minoru ...
JCAL
1998
57views more  JCAL 1998»
15 years 3 months ago
Fostering superficial learning
In this paper we discuss different views of learning and what it means to follow rules. The activities, the language and context of expertise and knowledge have traditionally ofte...
Robert Ramberg, Klas Karlgren
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
15 years 2 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
AAAI
2011
14 years 4 months ago
CCRank: Parallel Learning to Rank with Cooperative Coevolution
We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coev...
Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady Wiraw...
ICML
2003
IEEE
16 years 4 months ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon