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141
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SIGGRAPH
1994
ACM
15 years 6 months ago
Evolving virtual creatures
This paper describes a novel system for creating virtual creatures that move and behave in simulated three-dimensional physical worlds. The morphologies of creatures and the neura...
Karl Sims
120
Voted
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 6 months ago
On evolving buffer overflow attacks using genetic programming
In this work, we employed genetic programming to evolve a "white hat" attacker; that is to say, we evolve variants of an attack with the objective of providing better de...
Hilmi Günes Kayacik, Malcolm I. Heywood, A. N...
103
Voted
ICC
2008
IEEE
117views Communications» more  ICC 2008»
15 years 9 months ago
Proactive Power Optimization of Sensor Networks
—We propose a reduced-complexity genetic algorithm for dynamic deployment of resource constrained multi-hop mobile sensor networks. The goal of this paper is to achieve optimal c...
Rahul Khanna, Huaping Liu, Hsiao-Hwa Chen
157
Voted
NN
2007
Springer
267views Neural Networks» more  NN 2007»
15 years 2 months ago
Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization
In the last decade, recurrent neural networks (RNNs) have attracted more efforts in inferring genetic regulatory networks (GRNs), using time series gene expression data from micro...
Rui Xu, Ganesh K. Venayagamoorthy, Donald C. Wunsc...
197
Voted
GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 6 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto