public void TestRandomRestartHillClimberIncrementingRestartPoint()
{
comparer = new MaximizingComparer <TestIntegerEvaluableState>();
generator = new TestExponentialIntegerSuccessorGenerator();
var climberConfiguration = new ClimberConfiguration <TestIntegerEvaluableState, int>()
.ComparesUsing(comparer)
.GeneratesSuccessorsWith((c) => generator.GetSuccessors(c));
randomizer = new TestIntegerRandomizerSimulator();
climber = new RandomRestartHillClimber <TestIntegerEvaluableState, int>(5, randomizer, climberConfiguration);
RunTest(climber, 1, 10000);
}
public void TestRandomRestartHillClimberSameRestartPointEachTime()
{
comparer = new MaximizingComparer <TestIntegerEvaluableState>();
generator = new TestLinearIntegerSuccessorGenerator();
randomizer = new TestIntegerEvaluableStateNonRandomizer();
var climberConfiguration = new ClimberConfiguration <TestIntegerEvaluableState, int>()
.ComparesUsing(comparer)
.GeneratesSuccessorsWith((c) => generator.GetSuccessors(c));
randomizer = new TestIntegerEvaluableStateNonRandomizer();
climber = new RandomRestartHillClimber <TestIntegerEvaluableState, int>(5, randomizer, climberConfiguration);
RunTest(climber, 2, 100);
}
/// <summary>
/// Creates a new ClimberAlgorithm using the given comparison strategy to compare
/// evaluations and the given successorPicker to select the next EvaluableState to
/// evaluate against.
/// </summary>
/// <param name="successorPicker">The successor picker to choose the next EvaluableState in to evaluate at an optimization step</param>
protected ClimberAlgorithm(ISuccessorSelector <TState, TEvaluation> successorPicker)
{
this.successorPicker = successorPicker;
}
/// <summary>
/// Creates a new NumericClimberAlgorithm using the given comparison strategy to compare
/// discrete evaluations and the given successorPicker to select the next EvaluableState to
/// evaluate against non-greedily
/// </summary>
/// <param name="successorPicker">The successor picker to choose the next EvaluableState in to evaluate at an optimization step</param>
///
public NumericClimberAlgorithm(ISuccessorSelector <TState, int> successorPicker) : base(successorPicker)
{
}
/// <summary>
/// Creates a new <see cref="RandomRestartHillClimber{TState, TEvaluation}"/> that will perform numRestarts number of climber operations
/// </summary>
/// <param name="numRestarts">The number of climber operations to perform before returning a result</param>
/// <param name="stateRandomizer">A complex state randomization strategy</param>
/// <param name="climberConfiguration">A configuration for the climber that will be executed at each restart</param>
public RandomRestartHillClimber(uint numRestarts, ISuccessorSelector <TState, TEvaluation> stateRandomizer, IClimberConfiguration <TState, TEvaluation> climberConfiguration)
: this(numRestarts, climberConfiguration, c => stateRandomizer.Next(c))
{
}
/// <summary>
/// Create a new StateRandomizer with the given compaer, using the given SuccessorPicker that will perform
/// the given number of randomizations before returning a result. A numRanfomizations of -1 will have the optimier
/// return the first encountered optimal state
/// </summary>
/// <param name="evaluationComparer"></param>
/// <param name="successorPicker"></param>
/// <param name="numRandomizations"></param>
public StateRandomizer(IComparer <TState> evaluationComparer, ISuccessorSelector <TState, TEvaluation> successorPicker, int numRandomizations)
{
SuccessorPicker = successorPicker;
EvaluationComparer = evaluationComparer;
NumRandomizations = numRandomizations;
}
/// <summary>
/// Create a new StateRandomizer with the given compaer, using the given SuccessorPicker that will perform
/// a single randomization and return the most optimal result
/// </summary>
/// <param name="evaluationComparer"></param>
/// <param name="successorPicker"></param>
public StateRandomizer(IComparer <TState> evaluationComparer, ISuccessorSelector <TState, TEvaluation> successorPicker)
: this(evaluationComparer, successorPicker, 1)
{
}
/// <summary>
/// Creates a new LocalClimberAlgorithm using the given comparison strategy to compare
/// evaluations and the given successorPicker to select the next EvaluableState to
/// evaluate against
/// </summary>
/// <param name="successorPicker">The successor picker to choose the next EvaluableState in to evaluate at an optimization step</param>
///
public LocalClimberAlgorithm(ISuccessorSelector <TState, TEvaluation> successorPicker) : base(successorPicker)
{
}