Abstract: This chapter describes an application of genetic engineering-based genetic algorithms as a tool for knowledge acquisition and re-use. This version of genetic algorithms is based on a model of neo-Darwinian evolution enhanced by an analysis of genetic changes, which occur during evolution, and by application of various operations that genetically engineer new organisms using the results of this analysis. The genetic analysis is carried out using various machine learning methods. This analysis yields domain-specific knowledge in a form of two hierarchies of beneficial and detrimental genetic features. These features can then be re-used when similar problems are solved using genetic algorithms. Layout planning problem is used to demo...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...
Abstract: In this paper were presented the main directions of genetic algorithms. There is a large c...
The paper describes the application of a genetic engineering based extension to genetic algorithms t...
This paper presents a formal approach to the evolution of a representation for use in a design proce...
The chapter covers two main areas, these being an introduction to the technology and techniques asso...
This chapter reviews developments in genetic algorithms based on genetic engineering extensions. It ...
Abstract:- This paper presents a methodology for producing good design solutions more efficiently. T...
This paper describes research into the use of a genetic algorithm within a computer aided design too...
Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as adaptive technology to le...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
Genetic algorithms provide an approach to learning that is based loosely on simulated evolution. Hyp...
Genetic algorithms (GA) have several important features that predestine them to solve design problem...
University of Technology, Sydney. Faculty of Engineering and Information Technology.Evolutionary alg...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...
Abstract: In this paper were presented the main directions of genetic algorithms. There is a large c...
The paper describes the application of a genetic engineering based extension to genetic algorithms t...
This paper presents a formal approach to the evolution of a representation for use in a design proce...
The chapter covers two main areas, these being an introduction to the technology and techniques asso...
This chapter reviews developments in genetic algorithms based on genetic engineering extensions. It ...
Abstract:- This paper presents a methodology for producing good design solutions more efficiently. T...
This paper describes research into the use of a genetic algorithm within a computer aided design too...
Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as adaptive technology to le...
This paper provides a review on current developments in genetic algorithms. The discussion includes ...
Genetic algorithms provide an approach to learning that is based loosely on simulated evolution. Hyp...
Genetic algorithms (GA) have several important features that predestine them to solve design problem...
University of Technology, Sydney. Faculty of Engineering and Information Technology.Evolutionary alg...
Genetic programming (GP) is an automated method for creating a working computer program from a high-...
This paper provides an introduction to genetic algorithms and genetic programming and lists sources ...
Abstract: In this paper were presented the main directions of genetic algorithms. There is a large c...