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» Optimal Control with Adaptive Internal Dynamics Models
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GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 8 months ago
Stochastic training of a biologically plausible spino-neuromuscular system model
A primary goal of evolutionary robotics is to create systems that are as robust and adaptive as the human body. Moving toward this goal often involves training control systems tha...
Stanley Phillips Gotshall, Terence Soule
HYBRID
2010
Springer
15 years 11 months ago
Real-time scheduling of mixture-of-experts systems with limited resources
Mixture-of-Experts (MoE) systems solve intricate problems by combining results generated independently by multiple computational models (the “experts”). Given an instance of a...
Prapaporn Rattanatamrong, José A. B. Fortes
ICSE
1999
IEEE-ACM
15 years 8 months ago
Information Survivability Control Systems
We address the dependence of critical infrastructures— including electric power, telecommunications, finance and transportation—on vulnerable information systems. Our approach...
Kevin J. Sullivan, John C. Knight, Xing Du, Steve ...
ECAL
1995
Springer
15 years 8 months ago
Contemporary Evolution Strategies
After an outline of the history of evolutionary algorithms, a new ( ) variant of the evolution strategies is introduced formally. Though not comprising all degrees of freedom, it i...
Hans-Paul Schwefel, Günter Rudolph
GECCO
2004
Springer
150views Optimization» more  GECCO 2004»
15 years 9 months ago
Parameter Adaptation within Co-adaptive Learning Classifier Systems
The authors propose a co-adaptive approach to controlling parameters for coevolution-based learning classifier systems. By taking advantage of the on-line incremental learning capa...
Chung-Yuan Huang, Chuen-Tsai Sun