Corpus ID: 3109597

Designing Neural Networks Using Genetic Algorithms with Graph Generation System

@article{Kitano1990DesigningNN,
  title={Designing Neural Networks Using Genetic Algorithms with Graph Generation System},
  author={Hiroaki Kitano},
  journal={Complex Syst.},
  year={1990},
  volume={4}
}
  • H. Kitano
  • Published 1990
  • Mathematics, Computer Science
  • Complex Syst.
We present a new method of designing neural networks using the genetic algorithm. Recently there have been several reports claiming attempts to design neural networks using genetic algorithms were successful. However, these methods have a problem in scalability, i.e., the convergence characteristic degrades significantly as the size of the network increases. This is because these methods employ direct mapp ing of chromosomes into network connectivities. As an alternative approach, we propose a… Expand
A Review Of Methods For Encoding Neural Network Topologies In Evolutionary Computation
TLDR
The target of this review is to cover the main techniques of network encoding and make it easier to choose one when implementing a custom evolutionary algorithm for finding the network topology. Expand
Genetic Encoding of Neural Networks using Attribute Grammars
TLDR
A new grammatical encoding technique in which an attribute grammar is used to represent a class of neural networks is presented, and it is proposed that the resulting encoding offers several improvements over existing approaches. Expand
Genetic synthesis of Boolean neural networks with a cell rewriting developmental process
  • Frédéric Gruau
  • Mathematics
  • [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks
  • 1992
Genetic algorithms (GAS) are used to generate neural networks that implement Boolean functions. Neural networks both involve an architecture that is a graph of connections, and a set of weights. TheExpand
Searching neural network structures with L systems and genetic algorithms
TLDR
The conventional neural network model is modified so that it is easy to present the knowledge by birth and the learning by experience (dendrite weights) and a connection is shown to exist between the axon weights and learning parameters used e.g., in back propagation. Expand
Artificial Neural Network Development by means of Genetic Programming with Graph Codification
TLDR
This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs, which achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques. Expand
Evolving artificial neural network structure using grammar encoding and colonial competitive algorithm
TLDR
The proposed method uses grammatical encoding together with colonial competitive algorithm to evolve artificial neural network structure and parameters allowing the network architecture to shape the resulting search space in order to meet each problem requirement. Expand
A new metric for evaluating genetic optimization of neural networks
  • J. Dávila
  • Computer Science
  • 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks. Proceedings of the First IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (Cat. No.00
  • 2000
TLDR
An evaluation method that uses schema theory to aid the design of genetic codings for NN topology optimization and can help determine optimal balances between different evolutionary operators depending on the characteristics of the coding scheme is presented. Expand
Structure Design of Neural Networks Using Genetic Algorithms
A method for designing and training neural networks using genetic algorithms is proposed, with the aim of getting the optimal structure of the network and the optimized parameter set simultaneously.Expand
CELLULAR GRAPH GRAMMAR ENCODING OF NEURAL NETWORKS
  • 2011
This paper presents a novel approach to neural network evolution. Genomes used in this evolution are based on a well-described cellular encoding and a general mathematical idea of graph grammar.Expand
A comparison of matrix rewriting versus direct encoding for evolving neural networks
  • A. A. Siddiqi, S. Lucas
  • Computer Science
  • 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360)
  • 1998
TLDR
The authors present results that contradict findings, and demonstrate that a genetic algorithm (GA) using a direct encoding can find good individuals just as efficiently as a GA using matrix rewriting. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 20 REFERENCES
Developmental systems without cellular interactions, their languages and grammars.
TLDR
Theorems were obtained concerning partial characterizations of the class of developmental systems without cellular interactions, and some of the mathematical properties of this class are discussed. Expand
Optimal Brain Damage
TLDR
A class of practical and nearly optimal schemes for adapting the size of a neural network by using second-derivative information to make a tradeoff between network complexity and training set error is derived. Expand
Regressive events in neurogenesis.
TLDR
Far from being relatively minor aspects of neural development, regressive phenomena are now recognized as playing a major role in determining the form of the mature nervous system. Expand
Phoneme recognition using time-delay neural networks
The authors present a time-delay neural network (TDNN) approach to phoneme recognition which is characterized by two important properties: (1) using a three-layer arrangement of simple computingExpand
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
This book presents the official, formal definition of the programming language ML including the rules for grammar and static and dynamic semantics. ML is the most well-developed and prominent of aExpand
Selective stabilisation of developing synapses as a mechanism for the specification of neuronal networks
TLDR
The alternative proposed in this article is that connections are genetically specified between classes of cells, but the final wiring pattern depends on the refinement of those collections by selective stabilisation during neuronal activity. Expand
CHEMOAFFINITY IN THE ORDERLY GROWTH OF NERVE FIBER PATTERNS AND CONNECTIONS.
  • R. Sperry
  • Biology, Medicine
  • Proceedings of the National Academy of Sciences of the United States of America
  • 1963
TLDR
The hypothesis, 18-24 in brief, suggested that the patterning of synaptic connections in the nerve centers must be handled instead by the growth mechanism directly, independently of function, and with very strict selectivity governing synaptic formation from the beginning. Expand
The development of synapses in the visual system of the cat
  • B. Cragg
  • Biology, Medicine
  • The Journal of comparative neurology
  • 1975
TLDR
The gradual separation of neurones by neuropil during development precedes a parallel increase in the density of synapses by about one week, which rises to a peak of about 13,000 at seven weeks after birth and falls to slightly lower values in adult cats as the glial cells continue to develop. Expand
Development of neuronal specificity in retinal ganglion cells of Xenopus.
TLDR
The hypothesis is advanced of stepwise specification of progressively finer details of the pattern of neuronal connections; the initial steps occurring at an early stage of neuroblast differentiation before the outgrowth of neuronal processes. Expand
The Cascade-Co rrelation Learning Architecture
  • The Cascade-Co rrelation Learning Architecture
  • 1990
...
1
2
...