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EWRL
2008
15 years 8 months ago
Policy Learning - A Unified Perspective with Applications in Robotics
Policy Learning approaches are among the best suited methods for high-dimensional, continuous control systems such as anthropomorphic robot arms and humanoid robots. In this paper,...
Jan Peters, Jens Kober, Duy Nguyen-Tuong
IJCAI
2007
15 years 8 months ago
Bayesian Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Deepak Ramachandran, Eyal Amir
ICMLA
2008
15 years 8 months ago
Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
Sertan Girgin, Philippe Preux
MM
2004
ACM
167views Multimedia» more  MM 2004»
16 years 9 days ago
Learning an image manifold for retrieval
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
Xiaofei He, Wei-Ying Ma, HongJiang Zhang
ICIP
2000
IEEE
16 years 8 months ago
Incremental Shape Reconstruction Using Stereo Image Sequences
The limitations of estimating structure from either stereo or motion alone can be addressed by the use of stereo image sequences; however, many existing techniques for processing ...
Tai Jing Moyung, Paul W. Fieguth