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source: branches/CMAES/HeuristicLab.Algorithms.CMAEvolutionStrategy/3.3/StrategyVectorManipulator.cs @ 9115

Last change on this file since 9115 was 9115, checked in by abeham, 11 years ago

#1961: Added CMA-ES branch

File size: 4.2 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using HeuristicLab.Core;
23using HeuristicLab.Operators;
24using HeuristicLab.Optimization;
25using HeuristicLab.Parameters;
26using HeuristicLab.Encodings.RealVectorEncoding;
27using HeuristicLab.Data;
28using HeuristicLab.Random;
29using System;
30
31namespace HeuristicLab.Algorithms.EvolutionStrategy {
32  /// <summary>
33  /// Mutates the endogenous strategy parameters.
34  /// </summary>
35  public class StrategyVectorManipulator : SingleSuccessorOperator, IStochasticOperator {
36    public ILookupParameter<IRandom> RandomParameter {
37      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
38    }
39    public ILookupParameter<RealVector> StrategyVectorParameter {
40      get { return (ILookupParameter<RealVector>)Parameters["StrategyVector"]; }
41    }
42    public IValueLookupParameter<DoubleValue> GeneralLearningRateParameter {
43      get { return (IValueLookupParameter<DoubleValue>)Parameters["GeneralLearningRate"]; }
44    }
45    public IValueLookupParameter<DoubleValue> LearningRateParameter {
46      get { return (IValueLookupParameter<DoubleValue>)Parameters["LearningRate"]; }
47    }
48    /// <summary>
49    /// Initializes a new instance of <see cref="StrategyVectorManipulator"/> with four
50    /// parameters (<c>Random</c>, <c>StrategyVector</c>, <c>GeneralLearningRate</c> and
51    /// <c>LearningRate</c>).
52    /// </summary>
53    public StrategyVectorManipulator()
54      : base() {
55      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
56      Parameters.Add(new LookupParameter<RealVector>("StrategyVector", "The strategy vector to manipulate."));
57      Parameters.Add(new ValueLookupParameter<DoubleValue>("GeneralLearningRate", "The general learning rate (tau0)."));
58      Parameters.Add(new ValueLookupParameter<DoubleValue>("LearningRate", "The learning rate (tau)."));
59    }
60
61    /// <summary>
62    /// Mutates the endogenous strategy parameters.
63    /// </summary>
64    /// <param name="random">The random number generator to use.</param>
65    /// <param name="vector">The strategy vector to manipulate.</param>
66    /// <param name="generalLearningRate">The general learning rate dampens the mutation over all dimensions.</param>
67    /// <param name="learningRate">The learning rate dampens the mutation in each dimension.</param>
68    public static void Apply(IRandom random, RealVector vector, double generalLearningRate, double learningRate) {
69      NormalDistributedRandom N = new NormalDistributedRandom(random, 0.0, 1.0);
70      double generalMultiplier = Math.Exp(generalLearningRate * N.NextDouble());
71      for (int i = 0; i < vector.Length; i++) {
72        vector[i] *= generalMultiplier * Math.Exp(learningRate * N.NextDouble());
73      }
74    }
75    /// <summary>
76    /// Mutates the endogenous strategy parameters.
77    /// </summary>
78    /// <remarks>Calls <see cref="OperatorBase.Apply"/> of base class <see cref="OperatorBase"/>.</remarks>
79    /// <inheritdoc select="returns"/>
80    public override IOperation Apply() {
81      RealVector strategyParams = StrategyVectorParameter.ActualValue;
82      if (strategyParams != null) { // only apply if there is a strategy vector
83        IRandom random = RandomParameter.ActualValue;
84        double tau0 = GeneralLearningRateParameter.ActualValue.Value;
85        double tau = LearningRateParameter.ActualValue.Value;
86        Apply(random, strategyParams, tau0, tau);
87      }
88      return base.Apply();
89    }
90  }
91}
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