MGA - Minimal Genetic Algorithm (1.1.0)
            Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.
             
            Release Notes
            For the purpose of demonstration, a web-app version of the model can be accessed via the following URL: 
http://modelingcommons.org/browse/one_model/5742#model_tabs_browse_nlw
            Associated Publications
            
         
    
    
        
        
            
        
        MGA - Minimal Genetic Algorithm 1.1.0
        
            
                Submitted by
                
                    Cosimo Leuci
                
            
            
                
                    Published Jan 30, 2020
                
            
            
                Last modified Dec 05, 2024
            
         
        
        
            
                Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.
             
            
                
                
                
            
            
            Release Notes
            
                
For the purpose of demonstration, a web-app version of the model can be accessed via the following URL: 
http://modelingcommons.org/browse/one_model/5742#model_tabs_browse_nlw