From 4f26361eb08aa09334d1eea0a124110c20d809ce Mon Sep 17 00:00:00 2001 From: Eduardo Pedroni Date: Sat, 18 Oct 2014 15:21:45 +0200 Subject: Moved javadocs to a different repository for hosting, updated README --- doc/jcgp/backend/modules/problem/BestFitness.html | 352 ---------------- .../modules/problem/DigitalCircuitProblem.html | 423 ------------------- doc/jcgp/backend/modules/problem/Problem.html | 464 --------------------- .../modules/problem/SymbolicRegressionProblem.html | 436 ------------------- .../modules/problem/TestCaseProblem.TestCase.html | 320 -------------- .../backend/modules/problem/TestCaseProblem.html | 415 ------------------ .../modules/problem/TravellingSalesmanProblem.html | 433 ------------------- .../modules/problem/class-use/BestFitness.html | 212 ---------- .../problem/class-use/DigitalCircuitProblem.html | 124 ------ .../backend/modules/problem/class-use/Problem.html | 208 --------- .../class-use/SymbolicRegressionProblem.html | 124 ------ .../class-use/TestCaseProblem.TestCase.html | 251 ----------- .../modules/problem/class-use/TestCaseProblem.html | 227 ---------- .../class-use/TravellingSalesmanProblem.html | 124 ------ .../backend/modules/problem/package-frame.html | 28 -- .../backend/modules/problem/package-summary.html | 191 --------- doc/jcgp/backend/modules/problem/package-tree.html | 163 -------- doc/jcgp/backend/modules/problem/package-use.html | 311 -------------- 18 files changed, 4806 deletions(-) delete mode 100644 doc/jcgp/backend/modules/problem/BestFitness.html delete mode 100644 doc/jcgp/backend/modules/problem/DigitalCircuitProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/Problem.html delete mode 100644 doc/jcgp/backend/modules/problem/SymbolicRegressionProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/TestCaseProblem.TestCase.html delete mode 100644 doc/jcgp/backend/modules/problem/TestCaseProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/BestFitness.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/DigitalCircuitProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/Problem.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/SymbolicRegressionProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/TestCaseProblem.TestCase.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/TestCaseProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/class-use/TravellingSalesmanProblem.html delete mode 100644 doc/jcgp/backend/modules/problem/package-frame.html delete mode 100644 doc/jcgp/backend/modules/problem/package-summary.html delete mode 100644 doc/jcgp/backend/modules/problem/package-tree.html delete mode 100644 doc/jcgp/backend/modules/problem/package-use.html (limited to 'doc/jcgp/backend/modules/problem') diff --git a/doc/jcgp/backend/modules/problem/BestFitness.html b/doc/jcgp/backend/modules/problem/BestFitness.html deleted file mode 100644 index 4d19d5c..0000000 --- a/doc/jcgp/backend/modules/problem/BestFitness.html +++ /dev/null @@ -1,352 +0,0 @@ - - - - - -BestFitness - - - - - - - - -
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Enum BestFitness

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    All Implemented Interfaces:
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    java.io.Serializable, java.lang.Comparable<BestFitness>
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    public enum BestFitness
-extends java.lang.Enum<BestFitness>
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    Enum type to allow problems to indicate their fitness - orientation. -

    - BestFitness.HIGH means high fitness values are - better than low. Conversely, BestFitness.LOW - signals that low fitness values indicate better fitness - than high values.
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    Author:
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    Eduardo Pedroni
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      Enum Constant Summary

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      Enum Constants 
      Enum Constant and Description
      HIGH 
      LOW 
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      Method Summary

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      All Methods Static Methods Concrete Methods 
      Modifier and TypeMethod and Description
      static BestFitnessvalueOf(java.lang.String name) -
      Returns the enum constant of this type with the specified name.
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      static BestFitness[]values() -
      Returns an array containing the constants of this enum type, in -the order they are declared.
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        Methods inherited from class java.lang.Enum

        -compareTo, equals, getDeclaringClass, hashCode, name, ordinal, toString, valueOf
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        Methods inherited from class java.lang.Object

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      Method Detail

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        values

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        public static BestFitness[] values()
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        Returns an array containing the constants of this enum type, in -the order they are declared. This method may be used to iterate -over the constants as follows: -
        -for (BestFitness c : BestFitness.values())
-    System.out.println(c);
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        Returns:
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        an array containing the constants of this enum type, in the order they are declared
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        valueOf

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        public static BestFitness valueOf(java.lang.String name)
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        Returns the enum constant of this type with the specified name. -The string must match exactly an identifier used to declare an -enum constant in this type. (Extraneous whitespace characters are -not permitted.)
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        Parameters:
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        name - the name of the enum constant to be returned.
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        Returns:
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        the enum constant with the specified name
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        Throws:
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        java.lang.IllegalArgumentException - if this enum type has no constant with the specified name
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        java.lang.NullPointerException - if the argument is null
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jcgp.backend.modules.problem
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Class DigitalCircuitProblem

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    public class DigitalCircuitProblem
-extends TestCaseProblem<UnsignedInteger>
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    Digital circuit problem -

    - Using this problem type, digital logic circuits can be evolved. - parseData() must be used to load the desired circuit - truth table in the standard CGP .plu format.
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    Author:
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    Eduardo Pedroni
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    See Also:
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    DigitalCircuitFunctions
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      Constructor Detail

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        DigitalCircuitProblem

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        public DigitalCircuitProblem(Resources resources)
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        Construct a new instance of DigitalCircuitProblem.
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        Parameters:
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        resources - a reference to the experiment's resources.
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      Method Detail

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        evaluate

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        public void evaluate(Population population)
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        Description copied from class: Problem
        -
        The most important method of the problem type. This is called once - per generation, when the new population has been generated. -

        - The basic functionality of this method is to loop through all chromosomes - in the population and decode them according to the problem type. The - fitness of each chromosome is then calculated using the problem data - or otherwise (subjective problem types such as art generation might - leave fitness evaluations up to the user) and assigned to the appropriate - chromosome. -

        - In addition, realisations of this method should update the value of - bestFitness as appropriate, since the value of this parameter is displayed - if a GUI is in use.
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        Specified by:
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        evaluate in class Problem
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        Parameters:
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        population - the population to be evaluated.
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        parseTestCase

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        public TestCaseProblem.TestCase<UnsignedInteger> parseTestCase(java.lang.String[] inputs,
-                                                               java.lang.String[] outputs)
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        Description copied from class: TestCaseProblem
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        This method is used internally by addTestCase() in order - to appropriately parse strings into the right data type for the - test cases. Since the data type is problem-dependent, subclasses must - implement this method. This method must return a built TestCase - object from the arguments given.
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        Parameters:
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        inputs - the inputs represented as strings.
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        outputs - the outputs represented as strings.
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        Returns:
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        the parsed test case.
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        hasPerfectSolution

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        public int hasPerfectSolution(Population population)
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        Description copied from class: Problem
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        Used to assert whether a given population contains a perfect solution - to the problem. It is up to the problem to define what qualifies - a perfect solution, as some problems (subject ones such as music and - art evolution, for example) might not have perfect solutions at all.
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        Specified by:
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        hasPerfectSolution in class Problem
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        Parameters:
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        population - the population to search through for a perfect chromosome.
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        Returns:
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        the perfect solution index, if one exits, -1 if no perfect solution was found.
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jcgp.backend.modules.problem
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Class Problem

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    Direct Known Subclasses:
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    TestCaseProblem
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    public abstract class Problem
-extends Module
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    Defines the general behaviour of a CGP problem. The primary function of Problem - is to evaluate a population and assign a fitness value to each chromosome. -
    - Problems are free to define whether better fitness means a higher or lower fitness value. - In some problem types, it is more convenient to treat fitness 0 as the best possible value. - This can be done by changing the fitness orientation to BestFitness.HIGH or BestFitness.LOW as appropriate. - Fitness orientation is set to high by default. -

    - When extending this class, the constructor should call a few methods in order to - properly construct the problem type: setFunctionSet(), setFileExtension() and setFitnessOrientation(), - with the respective arguments. As with all subclasses of Module, setName() and - registerParameters() should be used where appropriate as well. -

    - It is advisable to use Resources.reportln() and Resources.report() - to print any relevant information. Note that reportln() and report() are affected - by the report interval base parameter. Use Resources.println() and - Resources.print() to print information regardless of the current generation. - See Resources for more information.
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    Author:
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    Eduardo Pedroni
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    See Also:
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    Module
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      Method Detail

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        evaluate

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        public abstract void evaluate(Population population)
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        The most important method of the problem type. This is called once - per generation, when the new population has been generated. -

        - The basic functionality of this method is to loop through all chromosomes - in the population and decode them according to the problem type. The - fitness of each chromosome is then calculated using the problem data - or otherwise (subjective problem types such as art generation might - leave fitness evaluations up to the user) and assigned to the appropriate - chromosome. -

        - In addition, realisations of this method should update the value of - bestFitness as appropriate, since the value of this parameter is displayed - if a GUI is in use.
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        Parameters:
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        population - the population to be evaluated.
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        hasPerfectSolution

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        public abstract int hasPerfectSolution(Population population)
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        Used to assert whether a given population contains a perfect solution - to the problem. It is up to the problem to define what qualifies - a perfect solution, as some problems (subject ones such as music and - art evolution, for example) might not have perfect solutions at all.
        -
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        Parameters:
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        population - the population to search through for a perfect chromosome.
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        Returns:
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        the perfect solution index, if one exits, -1 if no perfect solution was found.
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        hasImprovement

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        public abstract int hasImprovement(Population population)
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        Used to assert whether a given population has a chromosome that is an improvement over - the current best chromosome. A typical implementation of this method - will simply compare chromosome fitness values, though the problem type - is free to implement this in any way.
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        Parameters:
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        population - the population potentially containing a fitter chromosome.
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        Returns:
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        the index of the first chromosome in the population that is an improvement, -1 if none is found.
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        parseProblemData

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        public abstract void parseProblemData(java.io.File file,
-                                      ModifiableResources resources)
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        Parses the specified file and uses the parsed data to - set up the problem type instance appropriately. Any necessary - resource changes can be performed using the provided ModifiableResources - instance. -

        - In addition, realisations of this method should update the value of - maxFitness where appropriate, as this may be displayed to the user - if a GUI is in use.
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        Parameters:
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        file - the data file to parse.
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        resources - a modifiable reference to the experiment's resources.
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        getFunctionSet

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        public FunctionSet getFunctionSet()
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        the FunctionSet object used by this problem type.
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        getFileExtension

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        public java.lang.String getFileExtension()
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        Returns:
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        the file extension accepted by this problem type for problem data files.
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        getFitnessOrientation

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        public BestFitness getFitnessOrientation()
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        the fitness orientation of this particular problem.
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        getBestFitness

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        public double getBestFitness()
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        the current best fitness, in other words, the fitness - value of the fittest chromosome in the current generation.
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        reset

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        public void reset()
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        Resets the bestFitness parameter.
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jcgp.backend.modules.problem
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Class SymbolicRegressionProblem

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    public class SymbolicRegressionProblem
-extends TestCaseProblem<java.lang.Double>
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    Symbolic regression functions -

    - Using this problem type, regression problems can be solved. - parseData() must be used to load the desired function - data in the standard CGP .dat format. -

    - This problem uses quite a few parameters: -
      -
    • Error threshold: the maximum difference allowed between an - evolved output and the equivalent output from the problem data. - Outputs within the error threshold will be considered correct. - This is only used if hits is enabled.
      • -
    • Perfection threshold: if the fitness is calculated without - using the hits method, it is a decimal value. A solution is - considered perfect when the difference between its fitness and - the maximum possible fitness is within the perfection threshold.
      • -
    • Hits-based fitness: increment the fitness by 1 whenever the - chromosome output is within the error threshold.
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    Author:
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    Eduardo Pedroni
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    See Also:
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    SymbolicRegressionFunctions
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      Constructor Detail

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        SymbolicRegressionProblem

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        public SymbolicRegressionProblem(Resources resources)
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        Creates a new instance of SymbolicRegressionProblem.
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        Parameters:
        -
        resources - a reference to the experiment's resources.
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      Method Detail

      - - - -
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        evaluate

        -
        public void evaluate(Population population)
        -
        Description copied from class: Problem
        -
        The most important method of the problem type. This is called once - per generation, when the new population has been generated. -

        - The basic functionality of this method is to loop through all chromosomes - in the population and decode them according to the problem type. The - fitness of each chromosome is then calculated using the problem data - or otherwise (subjective problem types such as art generation might - leave fitness evaluations up to the user) and assigned to the appropriate - chromosome. -

        - In addition, realisations of this method should update the value of - bestFitness as appropriate, since the value of this parameter is displayed - if a GUI is in use.
        -
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        Specified by:
        -
        evaluate in class Problem
        -
        Parameters:
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        population - the population to be evaluated.
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        parseTestCase

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        public TestCaseProblem.TestCase<java.lang.Double> parseTestCase(java.lang.String[] inputs,
-                                                                java.lang.String[] outputs)
        -
        Description copied from class: TestCaseProblem
        -
        This method is used internally by addTestCase() in order - to appropriately parse strings into the right data type for the - test cases. Since the data type is problem-dependent, subclasses must - implement this method. This method must return a built TestCase - object from the arguments given.
        -
        -
        Parameters:
        -
        inputs - the inputs represented as strings.
        -
        outputs - the outputs represented as strings.
        -
        Returns:
        -
        the parsed test case.
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        hasPerfectSolution

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        public int hasPerfectSolution(Population population)
        -
        Description copied from class: Problem
        -
        Used to assert whether a given population contains a perfect solution - to the problem. It is up to the problem to define what qualifies - a perfect solution, as some problems (subject ones such as music and - art evolution, for example) might not have perfect solutions at all.
        -
        -
        Specified by:
        -
        hasPerfectSolution in class Problem
        -
        Parameters:
        -
        population - the population to search through for a perfect chromosome.
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        Returns:
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        the perfect solution index, if one exits, -1 if no perfect solution was found.
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jcgp.backend.modules.problem
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Class TestCaseProblem.TestCase<U>

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    U - the data type of the test case.
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    Enclosing class:
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    public static class TestCaseProblem.TestCase<U>
-extends java.lang.Object
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    Basic data type for encapsulating test cases, it simply - contains arrays of inputs and outputs and associated getters.
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    Author:
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    Eduardo Pedroni
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      Constructor Summary

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      Constructor and Description
      TestCase(U[] inputs, - U[] outputs) -
      Creates a new test case, inputs and outputs - must be specified upon instantiation.
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      Method Summary

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      Modifier and TypeMethod and Description
      U[]getInputs() 
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        TestCase

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        public TestCase(U[] inputs,
-                U[] outputs)
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        Creates a new test case, inputs and outputs - must be specified upon instantiation.
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        getInputs

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jcgp.backend.modules.problem
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Class TestCaseProblem<T>

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    Type Parameters:
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    T - the data type to be used by the TestCaseProblem.
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    Direct Known Subclasses:
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    DigitalCircuitProblem, SymbolicRegressionProblem
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    public abstract class TestCaseProblem<T>
-extends Problem
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    Abstract model for a problem that uses test cases. A test case - problem is any problem that compares the chromosome output to - an expected output taken from a table of input-output mappings. -

    - This class defines a basic data type for storing test cases, - TestCase, and provides core functionality to add and manipulate - test cases in the problem. A subclass of TestCaseProblem - must simply override parseTestCase() to convert parsed - problem data strings into the required data type (T).
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    Author:
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    Eduardo Pedroni
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    See Also:
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    Problem
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      Method Detail

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        getTestCases

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        public javafx.collections.ObservableList<TestCaseProblem.TestCase<T>> getTestCases()
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        a list containing the test cases.
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        addTestCase

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        public final void addTestCase(java.lang.String[] inputs,
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        Adds test cases to the problem instance as they get parsed from a - problem data file. This template method uses parseTestCase, which - must be implemented by subclasses.
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        Parameters:
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        inputs - the inputs represented as strings.
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        outputs - the outputs represented as strings.
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        clearTestCases

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        Remove all test cases.
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        parseProblemData

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        public void parseProblemData(java.io.File file,
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        Description copied from class: Problem
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        Parses the specified file and uses the parsed data to - set up the problem type instance appropriately. Any necessary - resource changes can be performed using the provided ModifiableResources - instance. -

        - In addition, realisations of this method should update the value of - maxFitness where appropriate, as this may be displayed to the user - if a GUI is in use.
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        Specified by:
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        parseProblemData in class Problem
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        file - the data file to parse.
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        resources - a modifiable reference to the experiment's resources.
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        hasImprovement

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        public int hasImprovement(Population population)
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        Description copied from class: Problem
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        Used to assert whether a given population has a chromosome that is an improvement over - the current best chromosome. A typical implementation of this method - will simply compare chromosome fitness values, though the problem type - is free to implement this in any way.
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        Specified by:
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        hasImprovement in class Problem
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        Parameters:
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        population - the population potentially containing a fitter chromosome.
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        Returns:
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        the index of the first chromosome in the population that is an improvement, -1 if none is found.
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- - - diff --git a/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html b/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html deleted file mode 100644 index 4a2d0c9..0000000 --- a/doc/jcgp/backend/modules/problem/TravellingSalesmanProblem.html +++ /dev/null @@ -1,433 +0,0 @@ - - - - - -TravellingSalesmanProblem - - - - - - - - -
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jcgp.backend.modules.problem
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Class TravellingSalesmanProblem

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    public class TravellingSalesmanProblem
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    Travelling salesman problem -

    - Using this problem type, travelling salesman tours can be evolved. - parseData() must be used to load the desired city - coordinates in the standard .tsp format.
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    Author:
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    Eduardo Pedroni
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    TravellingSalesmanFunctions
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        TravellingSalesmanProblem

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        public TravellingSalesmanProblem(Resources resources)
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        Construct a new instance of TravellingSalesmanProblem.
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        evaluate

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        public void evaluate(Population population,
-                     Resources resources)
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        Description copied from class: Problem
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        The most important method of the problem type. This is called once - per generation, when the new population has been generated. -

        - The basic functionality of this method is to loop through all chromosomes - in the population and decode them according to the problem type. The - fitness of each chromosome is then calculated using the problem data - or otherwise (subjective problem types such as art generation might - leave fitness evaluations up to the user) and assigned to the appropriate - chromosome. -

        - In addition, realisations of this method should update the value of - bestFitness as appropriate, since the value of this parameter is displayed - if a GUI is in use.
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        Specified by:
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        evaluate in class Problem
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        Parameters:
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        population - the population to be evaluated.
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        resources - parameters and utilities for optional reference.
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        isPerfectSolution

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        public boolean isPerfectSolution(Chromosome fittest)
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        Description copied from class: Problem
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        Used to assert whether a given chromosome is a perfect solution - to the problem. It is up to the problem to define what qualifies - a perfect solution, as some problems (subject ones such as music and - art evolution, for example) might not have perfect solutions at all. -

        - Note that if this method returns true, the experiment will move on - to the next run, or finish if no more runs are left.
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        Specified by:
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        isPerfectSolution in class Problem
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        fittest - the potentially perfect chromosome.
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        true if the argument is a perfect solution.
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        parseProblemData

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        public void parseProblemData(java.io.File file,
-                             ModifiableResources resources)
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        Description copied from class: Problem
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        Parses the specified file and uses the parsed data to - set up the problem type instance appropriately. Any necessary - resource changes can be performed using the provided ModifiableResources - instance. -

        - In addition, realisations of this method should update the value of - maxFitness where appropriate, as this may be displayed to the user - if a GUI is in use.
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        Specified by:
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        parseProblemData in class Problem
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        Parameters:
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        file - the data file to parse.
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        resources - a modifiable reference to the experiment's resources.
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        isImprovement

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        public boolean isImprovement(Chromosome fittest)
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        Description copied from class: Problem
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        Used to assert whether a given chromosome is an improvement over - the current best chromosome. A typical implementation of this method - will simply compare chromosome fitness values, though the problem type - is free to implement this in any way.
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        Specified by:
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        isImprovement in class Problem
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        Parameters:
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        fittest - the potentially fitter chromosome.
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