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GECCO
2010
Springer
248views Optimization» more  GECCO 2010»
15 years 9 months ago
Integrating decision space diversity into hypervolume-based multiobjective search
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Tamara Ulrich, Johannes Bader, Eckart Zitzler
ALMOB
2006
155views more  ALMOB 2006»
15 years 6 months ago
Refining motifs by improving information content scores using neighborhood profile search
The main goal of the motif finding problem is to detect novel, over-represented unknown signals in a set of sequences (e.g. transcription factor binding sites in a genome). The mo...
Chandan K. Reddy, Yao-Chung Weng, Hsiao-Dong Chian...
CPHYSICS
2006
204views more  CPHYSICS 2006»
15 years 6 months ago
Genetically controlled random search: a global optimization method for continuous multidimensional functions
A new stochastic method for locating the global minimum of a multidimensional function inside a rectangular hyperbox is presented. A sampling technique is employed that makes use ...
Ioannis G. Tsoulos, Isaac E. Lagaris
SIROCCO
2004
15 years 7 months ago
Improved Bounds for Optimal Black Hole Search with a Network Map
A black hole is a harmful host that destroys incoming agents without leaving any observable trace of such a destruction. The black hole search problem is to unambiguously determine...
Stefan Dobrev, Paola Flocchini, Nicola Santoro
LION
2007
Springer
192views Optimization» more  LION 2007»
16 years 17 days ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto