Sciweavers

1032 search results - page 109 / 207
» A Category of Explicit Fusions
Sort
View
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
14 years 2 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
GECCO
2007
Springer
153views Optimization» more  GECCO 2007»
14 years 2 months ago
Parallel genetic algorithm: assessment of performance in multidimensional scaling
Visualization of multidimensional data by means of Multidimensional Scaling (MDS) is a popular technique of exploratory data analysis widely usable, e.g. in analysis of bio-medica...
Antanas Zilinskas, Julius Zilinskas
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
14 years 2 months ago
Agent-environment interaction in a multi-agent system: a formal model
In this paper, we introduce a formal-language model for explicitly formalizing agent-environment interaction in a multiagent systems (MAS) framework: Conversational Grammar System...
Gemma Bel Enguix, Maria Dolores Jiménez-L&o...
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
14 years 2 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré