Class: NEAT::Controller

Inherits:

NeatOb

• Object
• NeatOb
• NEAT::Controller

show all

Defined in:

lib/rubyneat/rubyneat.rb

Overview

Defined Under Namespace

Classes: NeatSettings

Instance Attribute Summary (collapse)

• - (Object) compare_func

  Compare function for fitness Cost function for integrating in the cost to the fitness scalar.

• - (Object) cost_func

  Compare function for fitness Cost function for integrating in the cost to the fitness scalar.

• - (Object) end_run_func

  End run function to call at the end of each generational run Also report_hook to dump reports for the user, etc.

• - (Object) evaluator

  Returns the value of attribute evaluator.

• - (Object) evaluator_class

  Returns the value of attribute evaluator_class.

• - (Object) evolver

  Returns the value of attribute evolver.

• - (Object) evolver_class

  Returns the value of attribute evolver_class.

• - (Object) expressor

  Returns the value of attribute expressor.

• - (Object) expressor_class

  Returns the value of attribute expressor_class.

• - (Object) fitness_func

  Fitness function that Critters shall be rated on.

• - (Object) generation_num readonly

  Current generation count.

• - (Object) glob_innov_num readonly

  global innovation number.

• - (Object) log readonly

  Logger object for all of RubyNEAT.

• - (Object) neural_hidden

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

• - (Object) neural_inputs

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

• - (Object) neural_outputs

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

• - (Object) neuron_catalog

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

• - (Object) parms

  Parameters for evolution (NeatParameters).

• - (Object) population readonly

  population object and class specification.

• - (Object) population_class readonly

  population object and class specification.

• - (Object) population_history readonly

  population object and class specification.

• - (Object) query_func

  Query function that Critters shall call.

• - (Object) recurrence_func

  Recurrence function that Critters will yield to.

• - (Object) report_hook

  End run function to call at the end of each generational run Also report_hook to dump reports for the user, etc.

• - (Object) seq_num readonly

  current sequence number being evaluated.

• - (Object) stop_on_fit_func

  Compare function for fitness Cost function for integrating in the cost to the fitness scalar.

• - (Object) verbosity

  Global verbosity level: 1 - normal (the default) 2 - really verbose 3 - maximally verbose Use in conjunction with log.debug.

Attributes inherited from NeatOb

#controller, #name

Instance Method Summary (collapse)

• - (Object) gaussian
• - (Controller) initialize(neural_inputs: nil, neural_outputs: nil, neural_hidden: nil, parameters: NeatSettings.new, &block) constructor

  • 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.

• - (Object) new_innovation
• - (Object) run

  Run this evolution.

Methods inherited from NeatOb

log, #to_s

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

def initialize(neural_inputs: nil,
               neural_outputs: nil,
               neural_hidden: nil,
               parameters: NeatSettings.new,
                  &block)
  super(self)
  @verbosity = 1
  @glob_innov_num = 0
  @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

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# File 'lib/rubyneat/rubyneat.rb', line 197

def compare_func
  @compare_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 197

def cost_func
  @cost_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 201

def end_run_func
  @end_run_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 176

def evaluator
  @evaluator
end

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# File 'lib/rubyneat/rubyneat.rb', line 176

def evaluator_class
  @evaluator_class
end

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# File 'lib/rubyneat/rubyneat.rb', line 177

def evolver
  @evolver
end

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# File 'lib/rubyneat/rubyneat.rb', line 177

def evolver_class
  @evolver_class
end

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# File 'lib/rubyneat/rubyneat.rb', line 175

def expressor
  @expressor
end

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# File 'lib/rubyneat/rubyneat.rb', line 175

def expressor_class
  @expressor_class
end

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# File 'lib/rubyneat/rubyneat.rb', line 190

def fitness_func
  @fitness_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 160

def generation_num
  @generation_num
end

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# File 'lib/rubyneat/rubyneat.rb', line 154

def glob_innov_num
  @glob_innov_num
end

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# File 'lib/rubyneat/rubyneat.rb', line 204

def log
  @log
end

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# File 'lib/rubyneat/rubyneat.rb', line 167

def neural_hidden
  @neural_hidden
end

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# File 'lib/rubyneat/rubyneat.rb', line 167

def neural_inputs
  @neural_inputs
end

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# File 'lib/rubyneat/rubyneat.rb', line 167

def neural_outputs
  @neural_outputs
end

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# File 'lib/rubyneat/rubyneat.rb', line 163

def neuron_catalog
  @neuron_catalog
end

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# File 'lib/rubyneat/rubyneat.rb', line 170

def parms
  @parms
end

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# File 'lib/rubyneat/rubyneat.rb', line 173

def population
  @population
end

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# File 'lib/rubyneat/rubyneat.rb', line 173

def population_class
  @population_class
end

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# File 'lib/rubyneat/rubyneat.rb', line 173

def population_history
  @population_history
end

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# File 'lib/rubyneat/rubyneat.rb', line 187

def query_func
  @query_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 193

def recurrence_func
  @recurrence_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 201

def report_hook
  @report_hook
end

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# File 'lib/rubyneat/rubyneat.rb', line 157

def seq_num
  @seq_num
end

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# File 'lib/rubyneat/rubyneat.rb', line 197

def stop_on_fit_func
  @stop_on_fit_func
end

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# File 'lib/rubyneat/rubyneat.rb', line 184

def verbosity
  @verbosity
end

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# File 'lib/rubyneat/rubyneat.rb', line 368

def gaussian ; @gaussian.() ; end

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# File 'lib/rubyneat/rubyneat.rb', line 367

def new_innovation ; @glob_innov_num += 1; end

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

def run
  pre_run_initialize
  (1..@parms.max_generations).each do |gen_number|
    @generation_num = gen_number
    @population_history << unless @population.nil?
                             @population
                           else
                             @population = @population_class.new(self)
                           end
    @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 @verbosity < 3

    new_pop = @population.evolve

    ## Report hook for evaluation
    @report_hook.(@population.report) unless @report_hook.nil?

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

    ## Evolve population
    @population = new_pop

    ## Finish up this run
    @end_run_func.(self) unless @end_run_func.nil?
  end
end