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» Learning for control from multiple demonstrations
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IMR
2003
Springer
15 years 2 months ago
Multiple Stationary and Moving Boundary Handling in Cartesian Grids
A Cartesian grid generation methodology is developed for unsteady control volume computational fluid dynamic (CFD) solvers. Arbitrary combinations and numbers of moving and statio...
Kerem Pekkan

Publication
240views
13 years 8 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
ICRA
2006
IEEE
161views Robotics» more  ICRA 2006»
15 years 3 months ago
Quadruped Robot Obstacle Negotiation via Reinforcement Learning
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Sin...
80
Voted
IROS
2008
IEEE
115views Robotics» more  IROS 2008»
15 years 4 months ago
A framework for optimal gait generation via learning optimal control using virtual constraint
— This paper proposes an optimal gait generation framework using virtual constraint and learning optimal control. In this method, firstly, we add a constraint by a virtual poten...
Satoshi Satoh, Kenji Fujimoto, Sang-Ho Hyon
JAIR
2007
124views more  JAIR 2007»
14 years 9 months ago
Closed-Loop Learning of Visual Control Policies
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...
Sébastien Jodogne, Justus H. Piater