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EMO
2009
Springer
140views Optimization» more  EMO 2009»
13 years 11 months ago
On Using Populations of Sets in Multiobjective Optimization
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...
Johannes Bader, Dimo Brockhoff, Samuel Welten, Eck...
ECCC
2011
234views ECommerce» more  ECCC 2011»
13 years 1 months ago
On the complexity of computational problems regarding distributions (a survey)
We consider two basic computational problems regarding discrete probability distributions: (1) approximating the statistical difference (aka variation distance) between two given d...
Oded Goldreich, Salil P. Vadhan
JMLR
2008
92views more  JMLR 2008»
13 years 6 months ago
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...
Liviu Panait, Karl Tuyls, Sean Luke
GECCO
2007
Springer
190views Optimization» more  GECCO 2007»
14 years 27 days ago
Interactive evolutionary multi-objective optimization and decision-making using reference direction method
In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMO procedure to develop an algorit...
Kalyanmoy Deb, Abhishek Kumar
GECCO
2007
Springer
157views Optimization» more  GECCO 2007»
14 years 27 days ago
Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover
Multiobjective optimization problems with many local Pareto fronts is a big challenge to evolutionary algorithms. In this paper, two operators, biased initialization and biased cr...
Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sen...