When applying a Genetic Algorithm to a new problem, how many generations should one reasonably expect to wait before reaching an acceptable solution? Using arguments based on information flow into the genepool, mediated by selection each generation, we present a rough and ready heuristic. The Problem You have encoded a new problem for solution by Genetic Algorithm (GA) in what you hope is a sensible manner, using a population size and mutation rates that appear appropriate. Yet after 10,000 generations you are nowhere near reaching an acceptable solution; was that long enough to wait? The textbooks and standard literature provide surprisingly little advice on this crucial matter. Using arguments inspired by information-theoretic approaches ...
Living organisms are consummate problem solvers. They exhibit a versatility that puts the best compu...
We use an information theory approach to investigate the role of mutation on Genetic Algorithms (GA)...
A genetic algorithm (GA) is a meta-heuristic computation method that is inspired by Darwin's theory ...
A genetic algorithm is a technique designed to search large problem spaces using the Darwinian conce...
Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expres...
Evolutionary computing has been used for many years in the form of evolutionary algorithms (EA)---of...
It is difficult to predict a genetic algorithm's behavior on an arbitrary problem. Combining ge...
A fundamental question in biology is the following: what is the time scale that is needed for evolut...
<div><p>A fundamental question in biology is the following: what is the time scale that is needed fo...
this paper departs from standard GA orthodoxy, as from now on I shall concentrate on SAGA (Species A...
Abstract: In this paper were presented the main directions of genetic algorithms. There is a large c...
Neo-Darwinism can be usefully studied with the help of a Computerised Genetic Algorithm. Only a math...
Inspired by Darwin’s ideas, Turing (1948) proposed an evolutionary search as an automated problem so...
The majority of current genetic algorithms (GAs), while inspired by natural evolutionary systems, ar...
Introduction to Genetic Algorithms John Holland's pioneering book Adaptation in Natural and Ar...
Living organisms are consummate problem solvers. They exhibit a versatility that puts the best compu...
We use an information theory approach to investigate the role of mutation on Genetic Algorithms (GA)...
A genetic algorithm (GA) is a meta-heuristic computation method that is inspired by Darwin's theory ...
A genetic algorithm is a technique designed to search large problem spaces using the Darwinian conce...
Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expres...
Evolutionary computing has been used for many years in the form of evolutionary algorithms (EA)---of...
It is difficult to predict a genetic algorithm's behavior on an arbitrary problem. Combining ge...
A fundamental question in biology is the following: what is the time scale that is needed for evolut...
<div><p>A fundamental question in biology is the following: what is the time scale that is needed fo...
this paper departs from standard GA orthodoxy, as from now on I shall concentrate on SAGA (Species A...
Abstract: In this paper were presented the main directions of genetic algorithms. There is a large c...
Neo-Darwinism can be usefully studied with the help of a Computerised Genetic Algorithm. Only a math...
Inspired by Darwin’s ideas, Turing (1948) proposed an evolutionary search as an automated problem so...
The majority of current genetic algorithms (GAs), while inspired by natural evolutionary systems, ar...
Introduction to Genetic Algorithms John Holland's pioneering book Adaptation in Natural and Ar...
Living organisms are consummate problem solvers. They exhibit a versatility that puts the best compu...
We use an information theory approach to investigate the role of mutation on Genetic Algorithms (GA)...
A genetic algorithm (GA) is a meta-heuristic computation method that is inspired by Darwin's theory ...