#region License Information
/* HeuristicLab
* Copyright (C) 2002-2012 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Encodings.ConditionActionEncoding {
[Item("XCSAfterCrossoverOperator", "Description missing")]
[StorableClass]
public class XCSAfterCrossoverOperator : XCSAfterCopyingParentOperator {
#region Parameter Properties
public IValueLookupParameter TimestampParameter {
get { return (IValueLookupParameter)Parameters["Timestamp"]; }
}
public IValueLookupParameter PredictionParameter {
get { return (IValueLookupParameter)Parameters["Prediction"]; }
}
public IValueLookupParameter AverageActionSetSizeParameter {
get { return (IValueLookupParameter)Parameters["AverageActionSetSize"]; }
}
public IValueLookupParameter ErrorParameter {
get { return (IValueLookupParameter)Parameters["Error"]; }
}
public IValueLookupParameter FitnessParameter {
get { return (IValueLookupParameter)Parameters["Fitness"]; }
}
public ILookupParameter CurrentIterationParameter {
get { return (ILookupParameter)Parameters["CurrentIteration"]; }
}
public ILookupParameter> ParentAverageActionSetSizeParameter {
get { return (ILookupParameter>)Parameters["ParentAverageActionSetSize"]; }
}
public ILookupParameter> ParentPredictionParameter {
get { return (ILookupParameter>)Parameters["ParentPrediction"]; }
}
public ILookupParameter> ParentErrorParameter {
get { return (ILookupParameter>)Parameters["ParentError"]; }
}
public ILookupParameter> ParentFitnessParameter {
get { return (ILookupParameter>)Parameters["ParentFitness"]; }
}
#endregion
[StorableConstructor]
protected XCSAfterCrossoverOperator(bool deserializing) : base(deserializing) { }
protected XCSAfterCrossoverOperator(XCSAfterCrossoverOperator original, Cloner cloner)
: base(original, cloner) {
}
public XCSAfterCrossoverOperator()
: base() {
Parameters.Add(new ValueLookupParameter("Timestamp"));
Parameters.Add(new ValueLookupParameter("AverageActionSetSize"));
Parameters.Add(new ValueLookupParameter("Prediction"));
Parameters.Add(new ValueLookupParameter("Error"));
Parameters.Add(new ValueLookupParameter("Fitness"));
Parameters.Add(new LookupParameter("CurrentIteration"));
Parameters.Add(new ScopeTreeLookupParameter("ParentAverageActionSetSize"));
Parameters.Add(new ScopeTreeLookupParameter("ParentPrediction"));
Parameters.Add(new ScopeTreeLookupParameter("ParentError"));
Parameters.Add(new ScopeTreeLookupParameter("ParentFitness"));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new XCSAfterCrossoverOperator(this, cloner);
}
public override IOperation Apply() {
TimestampParameter.ActualValue = new IntValue(CurrentIterationParameter.ActualValue.Value);
var parentAverageActionSetSize = ParentAverageActionSetSizeParameter.ActualValue;
var parentPrecision = ParentPredictionParameter.ActualValue;
var parentPrecisionError = ParentErrorParameter.ActualValue;
var parentFitness = ParentFitnessParameter.ActualValue;
AverageActionSetSizeParameter.ActualValue = new DoubleValue(parentAverageActionSetSize.Select(x => x.Value).Average());
PredictionParameter.ActualValue = new DoubleValue(parentPrecision.Select(x => x.Value).Average());
ErrorParameter.ActualValue = new DoubleValue(0.25 * parentPrecisionError.Select(x => x.Value).Average());
FitnessParameter.ActualValue = new DoubleValue(0.1 * parentFitness.Select(x => x.Value).Average());
return base.Apply();
}
}
}