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» Graph Grammar Encoding and Evolution of Automata Networks
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ACSC
2005
IEEE
14 years 3 months ago
Graph Grammar Encoding and Evolution of Automata Networks
The global dynamics of automata networks (such as neural networks) are a function of their topology and the choice of automata used. Evolutionary methods can be applied to the opt...
Martin H. Luerssen
CEC
2005
IEEE
13 years 12 months ago
Graph composition in a graph grammar-based method for automata network evolution
The dynamics of neural and other automata networks are defined to a large extent by their topologies. Artificial evolution constitutes a practical means by which an optimal topolog...
Martin H. Luerssen, David M. W. Powers
GPEM
2006
82views more  GPEM 2006»
13 years 10 months ago
Shortcomings with using edge encodings to represent graph structures
There are various representations for encoding graph structures, such as artificial neural networks (ANNs) and circuits, each with its own strengths and weaknesses. Here we analyz...
Gregory Hornby
IJON
2008
88views more  IJON 2008»
13 years 10 months ago
Neural network construction and training using grammatical evolution
The term neural network evolution usually refers to network topology evolution leaving the network's parameters to be trained using conventional algorithms. In this paper we ...
Ioannis G. Tsoulos, Dimitris Gavrilis, Euripidis G...
ICSE
2001
IEEE-ACM
14 years 2 months ago
Encoding Program Executions
Dynamic analysis is based on collecting data as the program runs. However, raw traces tend to be too voluminous and too unstructured to be used directly for visualization and unde...
Steven P. Reiss, Manos Renieris