use normal distribution on initial random individual creation
initial default range tweaked way down rename "POP" template parameter to "POPSIZE" added RunOneGeneration() method - generations can now be run one at a time added SetRange(i,min,max) method added a decent amount of comments through main algorithm and class declaration
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@@ -8,9 +8,8 @@
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namespace DE
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{
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template <unsigned int DIM, unsigned int POP=(DIM*10)>
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template <unsigned int DIM, unsigned int POPSIZE=(DIM*10)>
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class Engine
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{
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public:
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@@ -18,58 +17,69 @@ namespace DE
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Engine();
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virtual ~Engine();
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void Reset();
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const double* GetBest() const;
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void SetRange(double minimum, double maximum);
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void SetRange(unsigned int i, double minimum, double maximum);
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void SetRange(const Vector<DIM>& minimum, const Vector<DIM>& maximum);
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virtual double CalculateError(const double testcase[DIM], bool& stop) = 0;
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void Reset();
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bool Solve(unsigned int maxgenerations = 1000000000);
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bool RunOneGeneration();
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private:
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void Select(unsigned int candidate, unsigned int *r1 = 0, unsigned int *r2 = 0, unsigned int *r3 = 0, unsigned int *r4 = 0, unsigned int *r5 = 0);
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// randomly select unique individuals
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void Select(
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unsigned int candidate,
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unsigned int *r1 = 0,
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unsigned int *r2 = 0,
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unsigned int *r3 = 0,
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unsigned int *r4 = 0,
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unsigned int *r5 = 0
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);
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// print a single individual to stdout
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void Dump(const double& fitness, Vector<DIM>& individual) const;
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void MakeTrial_best1exp(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand1exp(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_randtobest1exp(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best2exp(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand2exp(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best1bin(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand1bin(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_randtobest1bin(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best2bin(unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand2bin(unsigned int candidate, Vector<DIM>& trial);
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private:
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// DE algorithm
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void MakeTrial_best1exp (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand1exp (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_randtobest1exp (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best2exp (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand2exp (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best1bin (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand1bin (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_randtobest1bin (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_best2bin (unsigned int candidate, Vector<DIM>& trial);
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void MakeTrial_rand2bin (unsigned int candidate, Vector<DIM>& trial);
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// constants, parameters
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static const double DEFAULTSCALE;
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static const double DEFAULTCROSSOVER;
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static const double DEFAULTRANGE;
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static const double BIGDOUBLE;
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double scale;
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double crossover;
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// entropy source
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Random prng;
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private:
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Random prng;
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// population
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Vector<DIM> best;
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Vector<DIM> minimum;
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Vector<DIM> maximum;
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Vector<DIM> population[POP];
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double fitness[POP];
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double scale;
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double crossover;
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Vector<DIM> mean;
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Vector<DIM> variance;
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Vector<DIM> population[POPSIZE];
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double fitness[POPSIZE];
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double bestfitness;
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};
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// algorithm state
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bool success;
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unsigned int generation;
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};
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};
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@@ -10,43 +10,44 @@
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#endif
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template <unsigned int DIM, unsigned int POP>
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const double DE::Engine<DIM,POP>::DEFAULTSCALE = 0.85;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTSCALE = 0.85;
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template <unsigned int DIM, unsigned int POP>
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const double DE::Engine<DIM,POP>::DEFAULTCROSSOVER = 1.0;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTCROSSOVER = 1.0;
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template <unsigned int DIM, unsigned int POP>
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const double DE::Engine<DIM,POP>::DEFAULTRANGE= 100.0;
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::DEFAULTRANGE= 0.1;
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template <unsigned int DIM, unsigned int POP>
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const double DE::Engine<DIM,POP>::BIGDOUBLE = 1.79e308; // close to max double
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template <unsigned int DIM, unsigned int POPSIZE>
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const double DE::Engine<DIM,POPSIZE>::BIGDOUBLE = 1.79e308; // close to max double
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template <unsigned int DIM, unsigned int POP>
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inline DE::Engine<DIM,POP>::Engine()
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::Engine()
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{
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// set defaults
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scale = DEFAULTSCALE;
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crossover = DEFAULTCROSSOVER;
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for ( unsigned int i=0;i<DIM;i++ )
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for ( unsigned int i=0;i<DIM;++i )
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{
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this->minimum[i] = -DEFAULTRANGE;
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this->maximum[i] = -(this->minimum[i]);
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this->mean[i] = 0.0;
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this->variance[i] = DEFAULTRANGE;
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}
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// create an initial population
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Reset();
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline DE::Engine<DIM,POP>::~Engine()
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template <unsigned int DIM, unsigned int POPSIZE>
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inline DE::Engine<DIM,POPSIZE>::~Engine()
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{
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::Reset()
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Reset()
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{
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// reset our best
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bestfitness = BIGDOUBLE;
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@@ -56,7 +57,7 @@ inline void DE::Engine<DIM,POP>::Reset()
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}
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// reset all vectors
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for ( unsigned int i=0;i<POP;i++ )
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for ( unsigned int i=0;i<POPSIZE;i++ )
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{
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// energy tied for worst
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fitness[i] = bestfitness;
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@@ -64,48 +65,72 @@ inline void DE::Engine<DIM,POP>::Reset()
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// make a new individual
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for ( unsigned int j=0;j<DIM;j++ )
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{
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population[i][j] = prng.RandDouble(minimum[j],maximum[j]);
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population[i][j] = prng.RandGaussian(mean[j],variance[j]);
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}
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}
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// reset state
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generation = 0;
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success = false;
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::SetRange(double minimum, double maximum)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(double minimum, double maximum)
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{
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for (unsigned int i=0;i<DIM;i++)
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{
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this->minimum[i] = minimum;
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this->maximum[i] = maximum;
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SetRange(i,minimum,maximum);
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}
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::SetRange(const Vector<DIM>& minimum, const Vector<DIM>& maximum)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(unsigned int i, double minimum, double maximum)
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{
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this->minimum = minimum;
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this->maximum = maximum;
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if (i<DIM)
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{
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this->mean[i] = (maximum+minimum)/2.0;
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this->variance[i] = (maximum-minimum)/2.0;
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}
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline const double* DE::Engine<DIM,POP>::GetBest() const
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::SetRange(const Vector<DIM>& minimum, const Vector<DIM>& maximum)
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{
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for (unsigned int i=0;i<DIM;i++)
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{
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SetRange(i,minimum[i],maximum[i]);
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}
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return;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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inline const double* DE::Engine<DIM,POPSIZE>::GetBest() const
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{
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return best;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1, unsigned int *r2, unsigned int *r3, unsigned int *r4, unsigned int *r5)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Select(
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unsigned int candidate,
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unsigned int *r1,
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unsigned int *r2,
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unsigned int *r3,
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unsigned int *r4,
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unsigned int *r5
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)
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{
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if ( r1 )
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{
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do
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{
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*r1 = prng.RandU32(0,POP-1);
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*r1 = prng.RandU32(0,POPSIZE-1);
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}
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while ( *r1 == candidate );
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}
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@@ -114,7 +139,7 @@ inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1
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{
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do
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{
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*r2 = prng.RandU32(0,POP-1);
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*r2 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r2 == candidate) || (*r2 == *r1) );
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}
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@@ -123,7 +148,7 @@ inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1
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{
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do
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{
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*r3 = prng.RandU32(0,POP-1);
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*r3 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r3 == candidate) || (*r3 == *r2) || (*r3 == *r1) );
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}
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@@ -132,7 +157,7 @@ inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1
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{
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do
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{
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*r4 = prng.RandU32(0,POP-1);
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*r4 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r4 == candidate) || (*r4 == *r3) || (*r4 == *r2) || (*r4 == *r1) );
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}
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@@ -141,7 +166,7 @@ inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1
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{
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do
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{
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*r5 = prng.RandU32(0,POP-1);
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*r5 = prng.RandU32(0,POPSIZE-1);
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}
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while ( (*r5 == candidate) || (*r5 == *r4) || (*r5 == *r3) || (*r5 == *r2) || (*r5 == *r1) );
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}
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@@ -149,49 +174,66 @@ inline void DE::Engine<DIM,POP>::Select(unsigned int candidate, unsigned int *r1
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return;
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}
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// TODO: change this to run one generation at a time???
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template <unsigned int DIM, unsigned int POP>
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inline bool DE::Engine<DIM,POP>::Solve(unsigned int maxgenerations)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline bool DE::Engine<DIM,POPSIZE>::Solve(unsigned int maxgenerations)
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{
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bool success = false;
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// spawn a new generation
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Reset();
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for (unsigned int generation=0;generation<maxgenerations && !success;generation++)
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// run generations until max or success
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while(!success && generation<maxgenerations)
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{
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printf("====== GENERATION %07d =============================================\n\n",generation);
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success = RunOneGeneration();
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}
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for (int candidate=0;candidate<POP && !success;candidate++)
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// output
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printf("====== RUN COMPLETE =============================================\n\n");
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Dump(bestfitness,best);
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// finished
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return success;
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}
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template <unsigned int DIM, unsigned int POPSIZE>
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bool DE::Engine<DIM,POPSIZE>::RunOneGeneration()
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{
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printf("====== GENERATION %07d =============================================\n\n",++generation);
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// attempt to improve each individual in the population
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for (int candidate=0;candidate<POPSIZE && !success;candidate++)
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{
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// create a new trial individual to test
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Vector<DIM> trial;
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MakeTrial_randtobest1exp(candidate,trial);
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// determine fitness of trial individual
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double trialfitness = CalculateError(trial,success);
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// see if the trial improved current candidate in population
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if ( trialfitness < fitness[candidate] )
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{
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Vector<DIM> trial;
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MakeTrial_randtobest1exp(candidate,trial);
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// it did improve, save it
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fitness[candidate] = trialfitness;
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population[candidate] = trial;
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double trialfitness = CalculateError(trial,success);
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if ( trialfitness < fitness[candidate] )
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// see if it also improved upon our current best
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if ( trialfitness < bestfitness )
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{
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fitness[candidate] = trialfitness;
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population[candidate] = trial;
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// it's better than the best, save it
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bestfitness = trialfitness;
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best = trial;
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if ( trialfitness < bestfitness )
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{
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bestfitness = trialfitness;
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best = trial;
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Dump(bestfitness,best);
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}
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// output new best
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Dump(bestfitness,best);
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}
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}
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}
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printf("====== RUN COMPLETE =============================================\n\n");
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Dump(bestfitness,best);
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return success;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::Dump(const double& fitness, DE::Vector<DIM>& individual) const
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::Dump(const double& fitness, DE::Vector<DIM>& individual) const
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{
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printf(" fitness = %24.16f\n",fitness);
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for (unsigned int i=0;i<DIM;i++)
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@@ -201,8 +243,8 @@ inline void DE::Engine<DIM,POP>::Dump(const double& fitness, DE::Vector<DIM>& in
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printf("\n");
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::MakeTrial_best1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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@@ -220,8 +262,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_best1exp(unsigned int candidate, DE::
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::MakeTrial_rand1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3;
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unsigned int n;
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@@ -239,8 +281,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_rand1exp(unsigned int candidate, DE::
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::MakeTrial_randtobest1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_randtobest1exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2;
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unsigned int n;
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@@ -258,8 +300,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_randtobest1exp(unsigned int candidate
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::MakeTrial_best2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4;
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unsigned int n;
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@@ -277,8 +319,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_best2exp(unsigned int candidate, DE::
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return;
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}
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template <unsigned int DIM, unsigned int POP>
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inline void DE::Engine<DIM,POP>::MakeTrial_rand2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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template <unsigned int DIM, unsigned int POPSIZE>
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inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand2exp(unsigned int candidate, DE::Vector<DIM>& trial)
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{
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unsigned int r1, r2, r3, r4, r5;
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unsigned int n;
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@@ -296,8 +338,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_rand2exp(unsigned int candidate, DE::
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return;
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}
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||||
template <unsigned int DIM, unsigned int POP>
|
||||
inline void DE::Engine<DIM,POP>::MakeTrial_best1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
template <unsigned int DIM, unsigned int POPSIZE>
|
||||
inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
{
|
||||
unsigned int r1, r2;
|
||||
unsigned int n;
|
||||
@@ -318,8 +360,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_best1bin(unsigned int candidate, DE::
|
||||
return;
|
||||
}
|
||||
|
||||
template <unsigned int DIM, unsigned int POP>
|
||||
inline void DE::Engine<DIM,POP>::MakeTrial_rand1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
template <unsigned int DIM, unsigned int POPSIZE>
|
||||
inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
{
|
||||
unsigned int r1, r2, r3;
|
||||
unsigned int n;
|
||||
@@ -340,8 +382,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_rand1bin(unsigned int candidate, DE::
|
||||
return;
|
||||
}
|
||||
|
||||
template <unsigned int DIM, unsigned int POP>
|
||||
inline void DE::Engine<DIM,POP>::MakeTrial_randtobest1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
template <unsigned int DIM, unsigned int POPSIZE>
|
||||
inline void DE::Engine<DIM,POPSIZE>::MakeTrial_randtobest1bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
{
|
||||
unsigned int r1, r2;
|
||||
unsigned int n;
|
||||
@@ -362,8 +404,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_randtobest1bin(unsigned int candidate
|
||||
return;
|
||||
}
|
||||
|
||||
template <unsigned int DIM, unsigned int POP>
|
||||
inline void DE::Engine<DIM,POP>::MakeTrial_best2bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
template <unsigned int DIM, unsigned int POPSIZE>
|
||||
inline void DE::Engine<DIM,POPSIZE>::MakeTrial_best2bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
{
|
||||
unsigned int r1, r2, r3, r4;
|
||||
unsigned int n;
|
||||
@@ -384,8 +426,8 @@ inline void DE::Engine<DIM,POP>::MakeTrial_best2bin(unsigned int candidate, DE::
|
||||
return;
|
||||
}
|
||||
|
||||
template <unsigned int DIM, unsigned int POP>
|
||||
inline void DE::Engine<DIM,POP>::MakeTrial_rand2bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
template <unsigned int DIM, unsigned int POPSIZE>
|
||||
inline void DE::Engine<DIM,POPSIZE>::MakeTrial_rand2bin(unsigned int candidate, DE::Vector<DIM>& trial)
|
||||
{
|
||||
unsigned int r1, r2, r3, r4, r5;
|
||||
unsigned int n;
|
||||
|
||||
@@ -25,6 +25,8 @@ namespace DE
|
||||
|
||||
double RandDouble();
|
||||
double RandDouble(double min, double max);
|
||||
|
||||
double RandGaussian(double mean, double variance);
|
||||
|
||||
u32 RandU32();
|
||||
u32 RandU32(u32 min, u32 max);
|
||||
|
||||
+10
@@ -50,6 +50,16 @@ inline double DE::Random::RandDouble(double min, double max)
|
||||
return ( RandDouble() * (max - min) + min );
|
||||
}
|
||||
|
||||
inline double DE::Random::RandGaussian(double mean, double variance)
|
||||
{
|
||||
double sum = 0.0;
|
||||
for (int i=0;i<12;++i)
|
||||
{
|
||||
sum += RandDouble();
|
||||
}
|
||||
return mean + ( variance * ( sum - 6.0 ) );
|
||||
}
|
||||
|
||||
inline DE::u32 DE::Random::RandU32()
|
||||
{
|
||||
return Rand();
|
||||
|
||||
@@ -0,0 +1,90 @@
|
||||
#include <cstdio>
|
||||
#include <cmath>
|
||||
|
||||
#include "de.h"
|
||||
|
||||
// the order of the polynomial (actually the number of coefficients, i.e. 1 = constant, 2 = line, etc.)
|
||||
#define NUM_COEFFICIENTS 7
|
||||
|
||||
// the function we're searching for
|
||||
double TargetFunction(double x)
|
||||
{
|
||||
//return 1.0 / (1.0 + exp(-4.9*x)); // Ken Stanley's NEAT activation
|
||||
return (1.0 / (1.0 + exp(-4.9*x)) - 0.5) * 2.0; // " " (signed version)
|
||||
//return (1.0 / (1.0 + exp(-x)) - 0.5) * 2.0; // signed sigmoid
|
||||
//return exp(-x*x); // gaussian
|
||||
//return tanh(x); // tanh
|
||||
//return (2.0/(1.0+exp(-x))-1.0); // tanh approximation
|
||||
//return (x<0.0 ? -1.0 : 1.0) * sqrt(abs(x)); // signed root
|
||||
//return sin(x); // sin
|
||||
}
|
||||
|
||||
|
||||
// a helper function used in calculating the polynomials
|
||||
double CalculatePiecewise(double x, int n_coeffs, const double coeffs[])
|
||||
{
|
||||
double abs_x = (x < 0.0 ? -x : x);
|
||||
const double* pcoeffs;
|
||||
if ( abs_x < coeffs[6] )
|
||||
pcoeffs = &coeffs[0];
|
||||
else
|
||||
pcoeffs = &coeffs[3];
|
||||
|
||||
return (pcoeffs[0] + pcoeffs[1]*abs_x + pcoeffs[2]*abs_x*abs_x) * (x < 0.0 ? -1.0 : 1.0);
|
||||
}
|
||||
|
||||
|
||||
// our DE implementation
|
||||
class PolySearch: public DE::Engine<NUM_COEFFICIENTS>
|
||||
{
|
||||
public:
|
||||
// this method is called by the DE::Engine::Solve() to test a single DE individual
|
||||
double CalculateError(const double testcase[NUM_COEFFICIENTS], bool& stop)
|
||||
{
|
||||
double error = 0.0;
|
||||
unsigned int test_count = 0;
|
||||
|
||||
// accumulate squared error
|
||||
for ( double i=-2.5;i<=2.5;i+=0.01 )
|
||||
{
|
||||
// test
|
||||
double test = CalculatePiecewise(i,NUM_COEFFICIENTS,testcase);
|
||||
double actual = TargetFunction(i);
|
||||
|
||||
// accumulate error^2
|
||||
double e = test - actual;
|
||||
error += e * e;
|
||||
|
||||
// inc test count (divisor to get from SE to MSE)
|
||||
test_count++;
|
||||
}
|
||||
|
||||
// convert SE to RMSE
|
||||
error = sqrt(error / (double)test_count);
|
||||
|
||||
// set stop flag if the error is really low
|
||||
if ( error < 0.0000001 )
|
||||
{
|
||||
stop = true;
|
||||
}
|
||||
|
||||
// done
|
||||
return error;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
// main program
|
||||
int main()
|
||||
{
|
||||
PolySearch de;
|
||||
|
||||
// setup, adjust from default range
|
||||
//de.SetRange(-0.1,0.1);
|
||||
|
||||
// reset, and run the DE
|
||||
de.Solve(1000);
|
||||
|
||||
// done
|
||||
return 0;
|
||||
}
|
||||
Reference in new issue
Block a user