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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 3 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
CGF
2010
106views more  CGF 2010»
13 years 10 months ago
Alleviating the Modifiable Areal Unit Problem within Probe-Based Geospatial Analyses
We present a probe-based interface for the exploration of the results of a geospatial simulation of urban growth. Because our interface allows the user great freedom in how they c...
Thomas Butkiewicz, Ross K. Meentemeyer, Douglas A....
IJCAI
2003
13 years 11 months ago
Definition and Complexity of Some Basic Metareasoning Problems
In most real-world settings, due to limited time or other resources, an agent cannot perform all potentially useful deliberation and information gathering actions. This leads to t...
Vincent Conitzer, Tuomas Sandholm
CDC
2009
IEEE
126views Control Systems» more  CDC 2009»
13 years 11 months ago
Support vector machine classifiers for sequential decision problems
Classification problems in critical applications such as health care or security often require very high reliability because of the high costs of errors. In order to achieve this r...
Eladio Rodriguez Diaz, David A. Castaon
GECCO
2004
Springer
122views Optimization» more  GECCO 2004»
14 years 3 months ago
An Improved Diversity Mechanism for Solving Constrained Optimization Problems Using a Multimembered Evolution Strategy
This paper presents an improved version of a simple evolution strategy (SES) to solve global nonlinear optimization problems. As its previous version, the approach does not require...
Efrén Mezura-Montes, Carlos A. Coello Coell...