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» Cooperative searching for stochastic targets
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TJS
2002
160views more  TJS 2002»
14 years 9 months ago
Adaptive Optimizing Compilers for the 21st Century
Historically, compilers have operated by applying a fixed set of optimizations in a predetermined order. We call such an ordered list of optimizations a compilation sequence. This...
Keith D. Cooper, Devika Subramanian, Linda Torczon
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
15 years 3 months ago
Mission planning for joint suppression of enemy air defenses using a genetic algorithm
In this paper we present a genetic algorithm applied to the problem of mission planning for Joint Suppression of Enemy Air Defenses (JSEAD) in support of air strike operations. Th...
Jeffrey P. Ridder, Jason C. HandUber
ALIFE
2004
14 years 9 months ago
Development and the Baldwin Effect
Baldwin's classic hypothesis states that behavioral plasticity can speed evolution by (a) smoothing the fitness landscape and (b) indirect genetic assimilation of acquired cha...
Keith L. Downing
CVPR
2008
IEEE
15 years 11 months ago
Object tracking and detection after occlusion via numerical hybrid local and global mode-seeking
Given an object model and a black-box measure of similarity between the model and candidate targets, we consider visual object tracking as a numerical optimization problem. During...
Zhaozheng Yin, Robert T. Collins
GECCO
2010
Springer
237views Optimization» more  GECCO 2010»
15 years 2 months ago
Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed
The well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a robust stochastic search algorithm for optimizing functions defined on a continuous search space RD ....
Anne Auger, Dimo Brockhoff, Nikolaus Hansen