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2007
176views Robotics» more  RSS 2007»
13 years 9 months ago
Active Policy Learning for Robot Planning and Exploration under Uncertainty
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
IROS
2008
IEEE
101views Robotics» more  IROS 2008»
14 years 2 months ago
Spatial macroscopic models of a bio-inspired robotic swarm algorithm
— We present a comparative study of two spatially resolved macroscopic models of an autonomous robotic swarm. In previous experiments, the collective behavior of 15 autonomous sw...
Heiko Hamann, Heinz Wörn, Karl Crailsheim, Th...
ICML
2001
IEEE
14 years 8 months ago
Learning Probabilistic Models of Relational Structure
Most real-world data is stored in relational form. In contrast, most statistical learning methods work with "flat" data representations, forcing us to convert our data i...
Lise Getoor, Nir Friedman, Daphne Koller, Benjamin...
IROS
2008
IEEE
123views Robotics» more  IROS 2008»
14 years 2 months ago
Learning predictive terrain models for legged robot locomotion
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
Christian Plagemann, Sebastian Mischke, Sam Prenti...
ENVSOFT
2007
80views more  ENVSOFT 2007»
13 years 7 months ago
Testing the PEARL model in the Netherlands and Sweden
The Plant Protection Product Directive (91/414/EEC) stresses the need of validated models to calculate predicted environmental concentrations. The use of models has become an unav...
Fayçal Bouraoui