<< previous answermath HOME   answermath en Español       Loan Calculator Find any Print, Poster next >>    
    Artificial Intelligence Tutorials: Data Mining Neural Networks Fuzzy Logic Genetic Algorithms     Tutoriales de Inteligencia artificial: Redes Neuronales  Lógica Fuzzy  Minería Datos Algoritmos Genéticos    
    Mental math Tips: Addition ▫ Subtraction Multiplication Division Sine Cosine Tangent       Tips cálculo mental: Suma  Resta  Multiplicación  División Seno Coseno  Tangente    
       
  Structure

Aside from some important parameters, the central idea of the algorithm is this:

1. At any given time we will have a set (a Generation) of possible and different solutions of the problem (individuals, or phenotypes) with their respective abstract representation (chromosomes, or genotype).

 
                 
      2. An evaluation of each solution based on how good it is, creates some kind of ranking. This “Fitness” quantification of the solutions is one of the most important parts of the algorithm.

3. We may decide to keep as members for the next generation some of the best individuals in the present one (Elitism).

4. A new generation of solutions (Offspring) is created with individuals that are obtained by the combination (Crossover) of two selected solutions of the previous generation (Parents).

5. Little changes to few randomly selected solutions provide alternative mechanisms to obtain new individuals (Mutation).
 
                 

 6. Once the new generation of solutions is available we need to evaluate them as in point # 2 in order to begin another cycle. The process will terminate as in many recursive routines: because time is out, no evolution is observed, or an acceptable solution is found.

 

     
Google
  Web http://www.answermath.com
   
 
 

| Home | Suggest a link  | Send Comments  | Disclaimer | PrivacyPolicy | Links | Help |

Copyright 2000 - wgonz @ email.com  - All  Rights   Reserved