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ICMLA
2007
13 years 7 months ago
Control of a re-entrant line manufacturing model with a reinforcement learning approach
This paper presents the application of a reinforcement learning (RL) approach for the near-optimal control of a re-entrant line manufacturing (RLM) model. The RL approach utilizes...
José A. Ramírez-Hernández, Em...
SAGA
2009
Springer
14 years 9 days ago
Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies
We propose a generic method for obtaining quickly good upper bounds on the minimal value of a multistage stochastic program. The method is based on the simulation of a feasible dec...
Boris Defourny, Damien Ernst, Louis Wehenkel
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
13 years 10 months ago
Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm
Abstract. This paper focuses on Active Learning with a limited number of queries; in application domains such as Numerical Engineering, the size of the training set might be limite...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
AUSAI
2004
Springer
13 years 11 months ago
Learning the Grammar of Distant Change in the World-Wide Web
One problem many Web users encounter is to keep track of changes of distant Web sources. Push services, informing clients about data changes, are frequently not provided by Web ser...
Dirk Kukulenz
GECCO
2006
Springer
142views Optimization» more  GECCO 2006»
13 years 9 months ago
Classifier prediction based on tile coding
This paper introduces XCSF extended with tile coding prediction: each classifier implements a tile coding approximator; the genetic algorithm is used to adapt both classifier cond...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...