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AAAI
2008
14 years 12 months ago
HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required
We describe HTN-MAKER, an algorithm for learning hierarchical planning knowledge in the form of decomposition methods for Hierarchical Task Networks (HTNs). HTNMAKER takes as inpu...
Chad Hogg, Héctor Muñoz-Avila, Ugur ...
RAS
2010
117views more  RAS 2010»
14 years 8 months ago
Extending BDI plan selection to incorporate learning from experience
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. We describe a novel BDI exe...
Dhirendra Singh, Sebastian Sardiña, Lin Pad...
IJCNN
2000
IEEE
15 years 2 months ago
Learning Fine Positioning of a Robot Manipulator Based on Gabor Wavelets
: A system for learning the pre-grasp positioning task for a robot manipulator is presented. The images delivered from a gripper mounted camera are analysed using Gabor filters wh...
Jörg A. Walter, Bert Arnrich, Christian Schee...
MVA
2007
14 years 11 months ago
Semi-supervised Incremental Learning of Manipulative Tasks
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
Zhe Li, Sven Wachsmuth, Jannik Fritsch, Gerhard Sa...
ICML
2009
IEEE
15 years 10 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint