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» Using Stochastic Grammars to Learn Robotic Tasks
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NPL
1998
135views more  NPL 1998»
13 years 8 months ago
Local Adaptive Subspace Regression
Abstract. Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as b...
Sethu Vijayakumar, Stefan Schaal
IROS
2008
IEEE
125views Robotics» more  IROS 2008»
14 years 3 months ago
Dynamic correlation matrix based multi-Q learning for a multi-robot system
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Hongliang Guo, Yan Meng
IJRR
2010
177views more  IJRR 2010»
13 years 7 months ago
Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain
Rough terrain autonomous navigation continues to pose a challenge to the robotics community. Robust navigation by a mobile robot depends not only on the individual performance of ...
David Silver, J. Andrew Bagnell, Anthony Stentz
TSMC
2002
129views more  TSMC 2002»
13 years 8 months ago
A distributed robotic control system based on a temporal self-organizing neural network
A distributed robot control system is proposed based on a temporal self-organizing neural network, called competitive and temporal Hebbian (CTH) network. The CTH network can learn ...
Guilherme De A. Barreto, Aluizio F. R. Araú...
ICML
2006
IEEE
14 years 9 months ago
Maximum margin planning
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinke...