#region License Information
/* HeuristicLab
* Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab 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 HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HEAL.Attic;
using HeuristicLab.Random;
namespace HeuristicLab.Problems.GeneticProgramming.LawnMower {
[StorableType("3F72F63C-CBEB-43BD-ADC0-B3F0AD58331B")]
[Creatable(CreatableAttribute.Categories.GeneticProgrammingProblems, Priority = 160)]
[Item("Lawn Mower Problem", "The lawn mower demo problem for genetic programming.")]
public class Problem : SymbolicExpressionTreeProblem {
private const string LawnWidthParameterName = "LawnWidth";
private const string LawnLengthParameterName = "LawnLength";
public IFixedValueParameter LawnWidthParameter {
get { return (IFixedValueParameter)Parameters[LawnWidthParameterName]; }
}
public IFixedValueParameter LawnLengthParameter {
get { return (IFixedValueParameter)Parameters[LawnLengthParameterName]; }
}
public override bool Maximization {
get { return true; }
}
#region item cloning and persistence
[StorableConstructor]
protected Problem(StorableConstructorFlag _) : base(_) { }
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserialization() { }
protected Problem(Problem original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) {
return new Problem(this, cloner);
}
#endregion
public Problem()
: base() {
Parameters.Add(new FixedValueParameter(LawnWidthParameterName, "Width of the lawn.", new IntValue(8)));
Parameters.Add(new FixedValueParameter(LawnLengthParameterName, "Length of the lawn.", new IntValue(8)));
var g = new SimpleSymbolicExpressionGrammar();
g.AddSymbols(new string[] { "Sum", "Prog" }, 2, 2);
g.AddSymbols(new string[] { "Frog" }, 1, 1);
g.AddTerminalSymbols(new string[] { "Left", "Forward" });
// initialize 20 ephemeral random constants in [0..32[
var fastRand = new FastRandom(314159);
for (int i = 0; i < 20; i++) {
g.AddTerminalSymbol(string.Format("{0},{1}", fastRand.Next(0, 32), fastRand.Next(0, 32)));
}
Encoding = new SymbolicExpressionTreeEncoding(g, 1000, 17);
}
public override void Analyze(ISymbolicExpressionTree[] trees, double[] qualities, ResultCollection results, IRandom random) {
const string bestSolutionResultName = "Best Solution";
var bestQuality = Maximization ? qualities.Max() : qualities.Min();
var bestIdx = Array.IndexOf(qualities, bestQuality);
if (!results.ContainsKey(bestSolutionResultName)) {
results.Add(new Result(bestSolutionResultName, new Solution(trees[bestIdx], LawnLengthParameter.Value.Value, LawnWidthParameter.Value.Value, bestQuality)));
} else if (((Solution)(results[bestSolutionResultName].Value)).Quality < qualities[bestIdx]) {
results[bestSolutionResultName].Value = new Solution(trees[bestIdx], LawnLengthParameter.Value.Value, LawnWidthParameter.Value.Value, bestQuality);
}
}
public override double Evaluate(ISymbolicExpressionTree tree, IRandom random) {
var length = LawnLengthParameter.Value.Value;
var width = LawnWidthParameter.Value.Value;
var lawn = Interpreter.EvaluateLawnMowerProgram(length, width, tree);
// count number of squares that have been mowed
int numberOfMowedCells = 0;
for (int i = 0; i < length; i++)
for (int j = 0; j < width; j++)
if (lawn[i, j]) {
numberOfMowedCells++;
}
return numberOfMowedCells;
}
}
}