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» Learning Models of Macrobehavior in Complex Adaptive Systems
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ENTCS
2008
106views more  ENTCS 2008»
14 years 9 months ago
Modelling Adaptive Systems in ForSyDe
Emerging architectures such as partially reconfigurable FPGAs provide a huge potential for adaptivity in the area of embedded systems. Since many system functions are only execute...
Ingo Sander, Axel Jantsch
DAGM
2010
Springer
14 years 10 months ago
Complex Motion Models for Simple Optical Flow Estimation
The selection of an optical flow method is mostly a choice from among accuracy, efficiency and ease of implementation. While variational approaches tend to be more accurate than lo...
Claudia Nieuwenhuis, Daniel Kondermann, Christoph ...
ECMDAFA
2009
Springer
119views Hardware» more  ECMDAFA 2009»
14 years 7 months ago
Managing Model Adaptation by Precise Detection of Metamodel Changes
Technological and business changes influence the evolution of software systems. When this happens, the software artifacts may need to be adapted to the changes. This need is rapidl...
Kelly Garcés, Frédéric Jouaul...
NIPS
1998
14 years 11 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
ICANN
2009
Springer
15 years 4 months ago
Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning
Model complexity is key concern to any artificial learning system due its critical impact on generalization. However, EC research has only focused phenotype structural complexity ...
Faustino J. Gomez, Julian Togelius, Jürgen Sc...