19 search results - page 2 / 4 » High Dimension Action Spaces in Robot Skill Learning |
AIIA
2007
Springer
13 years 11 months ago
2007
Springer
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
ICRA
2006
IEEE
13 years 11 months ago
2006
IEEE
This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
ICRA
2005
IEEE
13 years 10 months ago
2005
IEEE
— We present a semi-parametric control policy representation and use it to solve a series of nonholonomic control problems with input state spaces of up to 7 dimensions. A neares...
NIPS
1993
13 years 6 months ago
1993
Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensionalcontinuousstate-spaces. In high dimensions it is essential that learningdoes not...
IJHR
2008
13 years 4 months ago
2008
Motion planning for humanoids faces several challenging issues: high dimensionality of the configuration space, necessity to address balance constraints in single and double suppo...