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121
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CORR
2010
Springer
147views Education» more  CORR 2010»
15 years 2 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
105
Voted
ICML
2002
IEEE
16 years 3 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
Bernhard Hengst
ATAL
2006
Springer
15 years 6 months ago
Multi-robot learning with particle swarm optimization
We apply an adapted version of Particle Swarm Optimization to distributed unsupervised robotic learning in groups of robots with only local information. The performance of the lea...
Jim Pugh, Alcherio Martinoli
216
Voted
NLPRS
2001
Springer
15 years 7 months ago
Hierarchical Concept Description and Learning for Information Extraction
This paper addresses the problem of extracting information from textual documents, either normal documents or web pages. A new approach for extracting complicate information from ...
Luo Xiao, Dieter Wissmann, Michael Brown, Stefan J...
115
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ICML
2005
IEEE
16 years 3 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers