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SIGIR
2000
ACM
15 years 2 months ago
2000
ACM
This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train diffe...
AAAI
2008
14 years 12 months ago
2008
Hierarchical state decompositions address the curse-ofdimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, w...
ICALT
2006
IEEE
15 years 3 months ago
2006
IEEE
All books entitled “Learn … with 1000 exercises” have in common the same basic principle. They aim to supply enough material to students so that they may better understand t...
ICML
1994
IEEE
15 years 1 months ago
1994
IEEE
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
ICRA
2009
IEEE
15 years 4 months ago
2009
IEEE
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...