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» Learning humanoid reaching tasks in dynamic environments
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CE
2006
123views more  CE 2006»
14 years 9 months ago
Conceptual and socio-cognitive support for collaborative learning in videoconferencing environments
Studies have shown that videoconferencing is an effective medium for facilitating communication between parties who are separated by distance, particularly when learners are engag...
Bernhard Ertl, Frank Fischer, Heinz Mandl
AUSAI
2004
Springer
15 years 3 months ago
A Dynamic Allocation Method of Basis Functions in Reinforcement Learning
In this paper, we propose a dynamic allocation method of basis functions, an Allocation/Elimination Gaussian Softmax Basis Function Network (AE-GSBFN), that is used in reinforcemen...
Shingo Iida, Kiyotake Kuwayama, Masayoshi Kanoh, S...
IJCNN
2008
IEEE
15 years 4 months ago
Learning to select relevant perspective in a dynamic environment
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
Zhihui Luo, David A. Bell, Barry McCollum, Qingxia...
ROBIO
2006
IEEE
129views Robotics» more  ROBIO 2006»
15 years 3 months ago
Learning Utility Surfaces for Movement Selection
— Humanoid robots are highly redundant systems with respect to the tasks they are asked to perform. This redundancy manifests itself in the number of degrees of freedom of the ro...
Matthew Howard, Michael Gienger, Christian Goerick...
ICML
2009
IEEE
15 years 10 months ago
Trajectory prediction: learning to map situations to robot trajectories
Trajectory planning and optimization is a fundamental problem in articulated robotics. Algorithms used typically for this problem compute optimal trajectories from scratch in a ne...
Nikolay Jetchev, Marc Toussaint