This software class enables users to create and conduct experiments using algorithms and a population. It provides a convenient way to set up the experiment in a structured manner, allowing easy management of parameters and data visualization.
Algorithm::Evolutionary::Run is a software class specifically designed for configuring an experimental environment for algorithms and population. This Perl-based software offers a hassle-free solution to run an algorithm within a single integrated platform.
With the easy-to-use SYNOPSIS, it is possible to create an instance of Algorithm::Evolutionary::Run using a YAML configuration file, or alternatively, by passing parameters directly in a hash reference. The configuration settings allow for customization of parameters such as the fitness function, crossover and mutation rates, maximum number of generations, population size, and selection rates.
Once the algorithm is set up, Algorithm::Evolutionary::Run executes the entire experiment until completion, providing results that can be accessed through a call to the results method. Alternatively, it is possible to execute a single step using the step method.
Although currently limited to fitness functions within the A::E::F namespace and binary strings, Algorithm::Evolutionary::Run stands out as a tool for demo purposes and serves as a useful class example for other projects.
With the easy-to-use SYNOPSIS, it is possible to create an instance of Algorithm::Evolutionary::Run using a YAML configuration file, or alternatively, by passing parameters directly in a hash reference. The configuration settings allow for customization of parameters such as the fitness function, crossover and mutation rates, maximum number of generations, population size, and selection rates.
Once the algorithm is set up, Algorithm::Evolutionary::Run executes the entire experiment until completion, providing results that can be accessed through a call to the results method. Alternatively, it is possible to execute a single step using the step method.
Although currently limited to fitness functions within the A::E::F namespace and binary strings, Algorithm::Evolutionary::Run stands out as a tool for demo purposes and serves as a useful class example for other projects.
What's New
Version 0.67: N/A