Evolutionary Algorithm(s) in Erlang.
genetica is a finished project, but is neither idiomatic nor efficient: It was designed for learning both Erlang and subsymbolic AI. Considering its current state, you should not use this project for anything — It is just here so that I can be nostalgic in the future.
Genetica has a framework which allows one to create new modules and let them be
used in the main framework. This is done by following a protocol, which requires
following functions to be available: parse_args, a function taking the
arguments given to this module and converts it into "proper" arguments.
random_genotype_fn takes parsed argument as input and returns a function
generating random genotypes. genotype_to_phenotype_fn takes parsed arguments
as input and returns a function which converts a genotype to a phenotype (A
process). mutation_fn takes the input arguments as input and returns a mutated
genotype. analyze_fn takes the input arguments as input, and returns a
function which takes a list of phenotypes coupled with their fitness, and
returns a list of numbers which may later be processed.
Phenotype ! {Pid, {gtype}}
Sends a message to Pid on the form {Phenotype, gtype, Genotype}, where
Genotype is the genotype of the Phenotype.
Phenotype ! {Pid, {fitness, PopulationPids}}
Sends a message to Pid on the form {Phenotype, fitness, Fitness}, where
Fitness is the fitness of the Phenotype.
Phenotype ! {Pid, {crossover, OtherPhenotype}}
Performs a crossover of Phenotype and OtherPhenotype, and sends the genotype
of the crossover as a message on the form {Phenotype, crossover, Genotype} to
Pid.
Phenotype ! {Pid, {shutdown}}
Sends the message {Phenotype, shutdown} to Pid and shutdowns.
Copyright © 2013 Jean Niklas L'orange
Distributed under the Eclipse Public License, the same as Clojure.