Class: NEAT::Controller

Inherits:
NeatOb
  • Object
show all
Defined in:
lib/rubyneat/rubyneat.rb

Overview

Controller for all operations of RubyNEAT

This object contains all the specifications and details for evolving and evaluation of the RubyNEAT system. It is a type of “World”, if you will, for the entire enterprise.

Your application shall only have one Controller.

FIXME: The function hooks really should be able to take more FIXME: than one hook! we don’t need that functionality right FIXME: now. Also, the Controller ‘god’ object itself will need FIXME: to undergo some refactorization so that we can have many FIXME: of them for HyperNEAT, co-evolution, etc.

FIXME: An alternative approach would be to have demigod objects FIXME: where the controller would lord it over them all. Attention FIXME: must also be given to Rubinius and JRuby so that we can FIXME: run under multiple cores.

Defined Under Namespace

Classes: NeatSettings

Instance Attribute Summary collapse

Attributes inherited from NeatOb

#controller, #name

Instance Method Summary collapse

Methods inherited from NeatOb

attr_neat, log, #to_s

Constructor Details

#initialize(neural_inputs: nil, neural_outputs: nil, neural_hidden: nil, parameters: NeatSettings.new, &block) ⇒ Controller

  • neural_inputs – array of input classes

  • neural_outputs – array of output classes

  • parameters – NeatParameters object, or a path to a YAML file to create this.


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# File 'lib/rubyneat/rubyneat.rb', line 498

def initialize(neural_inputs: nil,
               neural_outputs: nil,
               neural_hidden: nil,
               parameters: NeatSettings.new,
                  &block)
  super(self)
  @gaussian = Distribution::Normal.rng
  @population_history = []
  @evolver = Evolver.new self
  @expressor = Expressor.new self

  @neuron_catalog = Neuron::neuron_types.clone
  @neural_inputs  = neural_inputs
  @neural_outputs = neural_outputs
  @neural_hidden  = neural_hidden

  # Default classes for population and operators, etc.
  @population_class = NEAT::Population
  @evaluator_class = NEAT::Evaluator
  @expressor_class = NEAT::Expressor
  @evolver_class = NEAT::Evolver

  # Handle the parameters parameter. :-)
  @parms = unless parameters.kind_of? String
             parameters
           else # load it from a file
             open(parameters, 'r') { |fd| YAML::load fd.read }
           end
  block.(self) unless block.nil?
end

Instance Attribute Details

#evaluator ⇒ Object

Returns the value of attribute evaluator.


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# File 'lib/rubyneat/rubyneat.rb', line 337

def evaluator
  @evaluator
end

#evaluator_class ⇒ Object

Returns the value of attribute evaluator_class.


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# File 'lib/rubyneat/rubyneat.rb', line 337

def evaluator_class
  @evaluator_class
end

#evolver ⇒ Object

Returns the value of attribute evolver.


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# File 'lib/rubyneat/rubyneat.rb', line 338

def evolver
  @evolver
end

#evolver_class ⇒ Object

Returns the value of attribute evolver_class.


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# File 'lib/rubyneat/rubyneat.rb', line 338

def evolver_class
  @evolver_class
end

#expressor ⇒ Object

Returns the value of attribute expressor.


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# File 'lib/rubyneat/rubyneat.rb', line 336

def expressor
  @expressor
end

#expressor_class ⇒ Object

Returns the value of attribute expressor_class.


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# File 'lib/rubyneat/rubyneat.rb', line 336

def expressor_class
  @expressor_class
end

#generation_num ⇒ Object (readonly)

Current generation count


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# File 'lib/rubyneat/rubyneat.rb', line 321

def generation_num
  @generation_num
end

#log ⇒ Object (readonly)

Logger object for all of RubyNEAT


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# File 'lib/rubyneat/rubyneat.rb', line 371

def log
  @log
end

#neural_hidden ⇒ Object

Class map of named input and output neurons (each critter will have instantiations of these) name: InputNeuralClass (usually InputNeuron)


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# File 'lib/rubyneat/rubyneat.rb', line 328

def neural_hidden
  @neural_hidden
end

#neural_inputs ⇒ Object

Class map of named input and output neurons (each critter will have instantiations of these) name: InputNeuralClass (usually InputNeuron)


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# File 'lib/rubyneat/rubyneat.rb', line 328

def neural_inputs
  @neural_inputs
end

#neural_outputs ⇒ Object

Class map of named input and output neurons (each critter will have instantiations of these) name: InputNeuralClass (usually InputNeuron)


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# File 'lib/rubyneat/rubyneat.rb', line 328

def neural_outputs
  @neural_outputs
end

#neuron_catalog ⇒ Object

catalog of neurons classes to use { weight => nclass, … }


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# File 'lib/rubyneat/rubyneat.rb', line 324

def neuron_catalog
  @neuron_catalog
end

#parms ⇒ Object

Parameters for evolution (NeatParameters)


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# File 'lib/rubyneat/rubyneat.rb', line 331

def parms
  @parms
end

#population ⇒ Object (readonly)

population object and class specification


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# File 'lib/rubyneat/rubyneat.rb', line 334

def population
  @population
end

#population_class ⇒ Object (readonly)

population object and class specification


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# File 'lib/rubyneat/rubyneat.rb', line 334

def population_class
  @population_class
end

#population_history ⇒ Object (readonly)

population object and class specification


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# File 'lib/rubyneat/rubyneat.rb', line 334

def population_history
  @population_history
end

#seq_num ⇒ Object (readonly)

current sequence number being evaluated


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# File 'lib/rubyneat/rubyneat.rb', line 318

def seq_num
  @seq_num
end

Instance Method Details

#gaussian ⇒ Object 


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# File 'lib/rubyneat/rubyneat.rb', line 530

def gaussian ; @gaussian.() ; end

#new_innovation ⇒ Object 


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# File 'lib/rubyneat/rubyneat.rb', line 529

def new_innovation ; self.glob_innov_num += 1 ; end

#run ⇒ Object

Run this evolution.


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# File 'lib/rubyneat/rubyneat.rb', line 533

def run
  pre_run_initialize
  (1..@parms.max_generations).each do |gen_number|
    @generation_num = gen_number # must be set first
    @population_history << unless @population.nil?
                             @population
                           else
                             @population = @population_class.new(self)
                           end
    @population.generation = gen_number
    @population_history.shift unless @population_history.size <= @parms.max_population_history
    @population.mutate!
    @population.express!

    ## Evaluate population
    @evaluator.ready_for_evaluation @population
    (@parms.start_sequence_at .. @parms.end_sequence_at).each do |snum|
      @seq_num = snum
      @population.evaluate!
    end

    @population.analyze!
    @population.speciate!

    $log.debug @population.dump_s unless self.verbosity < 3

    new_pop = @population.evolve

    ## Report hook for evaluation
    report_hooks(@population.report)

    ## Exit if fitness criteria is reached
    #FIXME handle this exit condition better!!!!!
    exit_neat if stop_on_fit_func_hook(@population.report.last[:fitness], self) unless stop_on_fit_func_none?

    ## Evolve population
    @population = new_pop

    ## Finish up this run
    end_run_hooks(self)
  end
end