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124
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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 5 months ago
A GP neutral function for the artificial ANT problem
This paper introduces a function that increases the amount of neutrality (inactive code in Genetic Programming) for the Artificial Ant Problem. The objective of this approach is t...
Esteban Ricalde, Katya Rodríguez-Váz...
109
Voted
CCCG
2010
15 years 2 months ago
Any monotone boolean function can be realized by interlocked polygons
We show how to construct interlocked collections of simple polygons in the plane that fall apart upon removing certain combinations of pieces. Precisely, interiordisjoint simple p...
Erik D. Demaine, Martin L. Demaine, Ryuhei Uehara
94
Voted
FLAIRS
2003
15 years 2 months ago
Learning from Reinforcement and Advice Using Composite Reward Functions
1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
Vinay N. Papudesi, Manfred Huber
125
Voted
IJHIS
2006
104views more  IJHIS 2006»
15 years 1 months ago
Incremental evolution strategy for function optimization
This paper presents a novel evolutionary approach for function optimization Incremental Evolution Strategy (IES). Two strategies are proposed. One is to evolve the input variables...
Sheng Uei Guan, Wenting Mo
111
Voted
SIAMSC
2008
237views more  SIAMSC 2008»
15 years 1 months ago
A Variational Shape Optimization Approach for Image Segmentation with a Mumford--Shah Functional
We introduce a novel computational method for a Mumford-Shah functional, which decomposes a given image into smooth regions separated by closed curves. Casting this as a shape opti...
Günay Dogan, Pedro Morin, Ricardo H. Nochetto