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» A framework for the description of evolutionary algorithms
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ATAL
2003
Springer
14 years 27 days ago
A selection-mutation model for q-learning in multi-agent systems
Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
Karl Tuyls, Katja Verbeeck, Tom Lenaerts
CEC
2007
IEEE
13 years 11 months ago
Evolution of classification rules for comprehensible knowledge discovery
This article, which lies within the data mining framework, proposes a method to build classifiers based on the evolution of rules. The method, named REC (Rule Evolution for Classif...
Emiliano Carreno, Guillermo Leguizamón, Nea...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 8 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang
IPPS
2008
IEEE
14 years 2 months ago
Towards a decentralized architecture for optimization
We introduce a generic framework for the distributed execution of combinatorial optimization tasks. Instead of relying on custom hardware (like dedicated parallel machines or clus...
Marco Biazzini, Mauro Brunato, Alberto Montresor
WECWIS
2006
IEEE
103views ECommerce» more  WECWIS 2006»
14 years 1 months ago
Toward Semantic Composition of Web Services with MOVE
This paper describes a software solution for the WSChallenge 2006. We introduce the MOVE framework that has been applied to this challenge. Also, the architecture, algorithms, and...
Jürgen Dorn, Albert Rainer, Peter Hrastnik