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UAI
2004
13 years 8 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
WSC
2004
13 years 8 months ago
Impact of Production Run Length on Supply Chain Performance
This paper documents an experiment designed to show the value of simulation in understanding the relationship between production run lengths and overall supply chain performance. ...
David J. Parsons, Robin J. Clark, Kevin L. Payette
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 7 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
AUTOMATICA
2006
104views more  AUTOMATICA 2006»
13 years 7 months ago
Identification of multi-input systems: variance analysis and input design issues
This paper examines the identification of multi-input systems. Motivated by an experiment design problem (should one excite the various inputs simultaneously or separately), we ex...
Michel Gevers, Ljubisa Miskovic, Dominique Bonvin,...
JMLR
2008
124views more  JMLR 2008»
13 years 7 months ago
Learning Control Knowledge for Forward Search Planning
A number of today's state-of-the-art planners are based on forward state-space search. The impressive performance can be attributed to progress in computing domain independen...
Sung Wook Yoon, Alan Fern, Robert Givan