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ECAL
2001
Springer
15 years 6 months ago
Pareto Optimality in Coevolutionary Learning
We develop a novel coevolutionary algorithm based upon the concept of Pareto optimality. The Pareto criterion is core to conventional multi-objective optimization (MOO) algorithms....
Sevan G. Ficici, Jordan B. Pollack
HCW
1999
IEEE
15 years 6 months ago
Multiple Cost Optimization for Task Assignment in Heterogeneous Computing Systems Using Learning Automata
A framework for task assignment in heterogeneous computing systems is presented in this work. The framework is based on a learning automata model. The proposed model can be used f...
Raju D. Venkataramana, N. Ranganathan
INFOCOM
2012
IEEE
13 years 4 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu
EURONGI
2005
Springer
15 years 7 months ago
An Afterstates Reinforcement Learning Approach to Optimize Admission Control in Mobile Cellular Networks
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
José Manuel Giménez-Guzmán, J...
COLT
2003
Springer
15 years 7 months ago
Learning All Subfunctions of a Function
Sublearning, a model for learning of subconcepts of a concept, is presented. Sublearning a class of total recursive functions informally means to learn all functions from that cla...
Sanjay Jain, Efim B. Kinber, Rolf Wiehagen