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GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 3 days ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
14 years 21 days ago
Multicriteria Network Design Using Evolutionary Algorithm
In this paper, we revisit a general class of multi-criteria multi-constrained network design problems and attempt to solve, in a novel way, with Evolutionary Algorithms (EAs). A ma...
Rajeev Kumar, Nilanjan Banerjee
CORR
2006
Springer
147views Education» more  CORR 2006»
13 years 7 months ago
ARQ Diversity in Fading Random Access Channels
A cross-layer optimization approach is adopted for the design of symmetric random access wireless systems. Instead of the traditional collision model, a more realistic physical la...
Young-Han Nam, Praveen Kumar Gopala, Hesham El Gam...
CISSE
2009
Springer
13 years 5 months ago
Optimal Component Selection for Component-Based Systems
In Component-based Software (CBS) development, it is desirable to choose software components that provide all necessary functionalities and at the same time optimize certain nonfun...
Muhammad Ali Khan, Sajjad Mahmood
MVA
2007
179views Computer Vision» more  MVA 2007»
13 years 7 months ago
Multi-object trajectory tracking
The majority of existing tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework using a Hidden Markov Model, where the distribution ...
Mei Han, Wei Xu, Hai Tao, Yihong Gong