mgo.evolution.neat.NEATProblem.scala Maven / Gradle / Ivy

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///*
// * Copyright (C) 2015 Guillaume Chérel
// *
// * This program is free software: you can redistribute it and/or modify
// * it under the terms of the GNU Affero General Public License as published by
// * the Free Software Foundation, either version 3 of the License, or
// * (at your option) any later version.
// *
// * This program is distributed in the hope that it will be useful,
// * but WITHOUT ANY WARRANTY; without even the implied warranty of
// * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// * GNU General Public License for more details.
// *
// * You should have received a copy of the GNU General Public License
// * along with this program.  If not, see .
// */
//
//package mgo.evolution.problem
//
//import mgo.evolution._
//import scala.util.Random
//import monocle.syntax._
//import mgo.tools.neuralnetwork._
//import collection.immutable.IntMap
//
//import mgo.tools.time
//
///**
// * Cake to define a problem for a genetic algorithm
// */
//trait NEATProblem extends Problem with NoPhenotype with NEATGenome with DoubleFitness {
//
//  type NN // <: NeuralNetwork[Any, Double, Double]
//
//  def evaluate(phenotype: P, rng: Random): F = evaluateNet(createNet(phenotype)(rng))(rng)
//
//  def createNet(phenotype: P)(implicit rng: Random): NN = {
//    // nodes indices in phenotypes may not be contiguous. Translate into contiguous indices
//    val nodes = phenotype.nodes.toVector.sortBy { case (index, node) => index }
//    val nodesMap = IntMap.empty ++ nodes.map { case (index, _) => index }.toSeq.sorted.zipWithIndex
//    createNet(
//      nodes.map { case (_, node) => node },
//      (inputNodesIndices ++ biasNodesIndices).map { nodesMap(_) },
//      outputNodesIndices.map { nodesMap(_) },
//      phenotype.connectionGenes.filter { _.enabled }.map { cg => (nodesMap(cg.inNode), nodesMap(cg.outNode), cg.weight) }
//    )
//  }
//
//  def createNet(
//    _nodes: IndexedSeq[Node],
//    _inputnodes: IndexedSeq[Int],
//    _outputnodes: IndexedSeq[Int],
//    _edges: Seq[(Int, Int, Double)])(implicit rng: Random): NN
//
//  def evaluateNet(n: NN)(implicit rng: Random): Double
//}