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IJCNN
2006
IEEE
14 years 1 months ago
Reinforcement Learning for Parameterized Motor Primitives
Abstract— One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement genera...
Jan Peters, Stefan Schaal

Publication
240views
12 years 6 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
COLT
2007
Springer
14 years 1 months ago
Minimax Bounds for Active Learning
This paper analyzes the potential advantages and theoretical challenges of “active learning” algorithms. Active learning involves sequential sampling procedures that use infor...
Rui Castro, Robert D. Nowak
ICPR
2004
IEEE
14 years 8 months ago
Periodic Nonlinear Principal Component Neural Networks for Humanoid Motion Segmentation, Generalization, and Generation
In an experiment with a soccer playing robot, periodic temporally-constrained nonlinear principal component neural networks (NLPCNNs) are shown to characterize humanoid motion eff...
Karl F. MacDorman, Rawichote Chalodhorn, Minoru As...
IAT
2009
IEEE
14 years 2 months ago
Agent-Based Security System for User Verification
—We present a security system consisting of an arbitrary number of entries, sensors and agents. The intelligent integrated system is based on user modeling, i.e. models of their ...
Erik Dovgan, Bostjan Kaluza, Tea Tusar, Matjaz Gam...