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» Using model knowledge for learning inverse dynamics
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126
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AUTOMATICA
2004
110views more  AUTOMATICA 2004»
15 years 3 months ago
Robust adaptive control of a class of nonlinear systems with unknown dead-zone
This paper deals with the adaptive control of a class of continuous-time nonlinear dynamic systems preceded by an unknown dead-zone. By using a new description of a dead-zone and ...
Xing-Song Wang, Chun-Yi Su, Henry Hong
KES
2005
Springer
15 years 9 months ago
Learning Within the BDI Framework: An Empirical Analysis
One of the limitations of the BDI (Belief-Desire-Intention) model is the lack of any explicit mechanisms within the architecture to be able to learn. In particular, BDI agents do n...
Toan Phung, Michael Winikoff, Lin Padgham
228
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AR
2011
14 years 10 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
207
Voted
MLMI
2007
Springer
15 years 9 months ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...
155
Voted
UAI
2008
15 years 4 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau