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GECCO
2000
Springer
141views Optimization» more  GECCO 2000»
15 years 10 months ago
A steady-state evolutionary algorithm for the job shop problem
This paper describes an evolutionary search scheduling algorithm (ESSA) for the job shop scheduling problem (JSSP). If no specific knowledge of the problem is included in the EA t...
Patrick van Bael, Dirk Devogelaere, Marcel Rijckae...
SEMWEB
2009
Springer
16 years 1 months ago
An Algorithm for Learning with Probabilistic Description Logics
Probabilistic Description Logics are the basis of ontologies in the Semantic Web. Knowledge representation and reasoning for these logics have been extensively explored in the last...
José Eduardo Ochoa Luna, Fabio Gagliardi Co...
TSMC
2008
132views more  TSMC 2008»
15 years 6 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
ICTAI
2006
IEEE
16 years 23 days ago
MI-Winnow: A New Multiple-Instance Learning Algorithm
We present MI-Winnow, a new multiple-instance learning (MIL) algorithm that provides a new technique to convert MIL data into standard supervised data. In MIL each example is a co...
Sharath R. Cholleti, Sally A. Goldman, Rouhollah R...
PODS
2010
ACM
170views Database» more  PODS 2010»
15 years 11 months ago
A learning algorithm for top-down XML transformations
A generalization from string to trees and from languages to translations is given of the classical result that any regular language can be learned from examples: it is shown that ...
Aurélien Lemay, Sebastian Maneth, Joachim N...