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FLAIRS
2008
13 years 10 months ago
State Space Compression with Predictive Representations
Current studies have demonstrated that the representational power of predictive state representations (PSRs) is at least equal to the one of partially observable Markov decision p...
Abdeslam Boularias, Masoumeh T. Izadi, Brahim Chai...
IJRR
2008
139views more  IJRR 2008»
13 years 7 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
TASE
2010
IEEE
13 years 2 months ago
Coverage of a Planar Point Set With Multiple Robots Subject to Geometric Constraints
This paper focuses on the assignment of discrete points among K robots and determining the order in which the points should be processed by the robots, in the presence of geometric...
Nilanjan Chakraborty, Srinivas Akella, John T. Wen
ICRA
2003
IEEE
119views Robotics» more  ICRA 2003»
14 years 29 days ago
HPRM: a hierarchical PRM
— We introduce a hierarchical variant of the probabilistic roadmap method for motion planning. By recursively refining an initially sparse sampling in neighborhoods of the C-obs...
Anne D. Collins, Pankaj K. Agarwal, John Harer
ATAL
2006
Springer
13 years 11 months ago
A hierarchical approach to efficient reinforcement learning in deterministic domains
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...