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» Modeling Sensorimotor Learning with Linear Dynamical Systems
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NIPS
1998
13 years 9 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
NPL
2007
109views more  NPL 2007»
13 years 7 months ago
Generative Modeling of Autonomous Robots and their Environments using Reservoir Computing
Autonomous mobile robots form an important research topic in the field of robotics due to their near-term applicability in the real world as domestic service robots. These robots ...
Eric A. Antonelo, Benjamin Schrauwen, Jan M. Van C...
NIPS
1994
13 years 9 months ago
Interference in Learning Internal Models of Inverse Dynamics in Humans
Experiments were performed to reveal some of the computational properties of the human motor memory system. We show that as humans practice reaching movements while interacting wi...
Reza Shadmehr, Tom Brashers-Krug, Ferdinando A. Mu...
AIPS
2006
13 years 9 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
JSW
2008
130views more  JSW 2008»
13 years 7 months ago
A Constraint-Driven Executable Model of Dynamic System Reconfiguration
Dynamic system reconfiguration techniques are presented that can enable the systematic evolution of software systems due to unanticipated changes in specification or requirements. ...
D'Arcy Walsh, Francis Bordeleau, Bran Selic