ggreedysearch.h

来自「一个由Mike Gashler完成的机器学习方面的includes neural」· C头文件 代码 · 共 130 行

/*
	Copyright (C) 2006, Mike Gashler

	This library is free software; you can redistribute it and/or
	modify it under the terms of the GNU Lesser General Public
	License as published by the Free Software Foundation; either
	version 2.1 of the License, or (at your option) any later version.

	see http://www.gnu.org/copyleft/lesser.html
*/

#ifndef __GGREEDYSEARCH_H__
#define __GGREEDYSEARCH_H__

#include "GSearch.h"

class GAVLTree;


// At each iteration this algorithm moves in only one
// dimension. If the situation doesn't improve it tries
// the opposite direction. If both directions are worse,
// it decreases the step size for that dimension, otherwise
// it increases the step size for that dimension.
class GMomentumGreedySearch : public GRealVectorSearch
{
protected:
	int m_nDimensions;
	int m_nCurrentDim;
	double* m_pStepSizes;
	double* m_pVector;
	double m_dError;
	double m_dChangeFactor;

public:
	GMomentumGreedySearch(GRealVectorCritic* pCritic);
	virtual ~GMomentumGreedySearch();

	// Set the current vector
	void SetState(double* pVector);

	// Set all the current step sizes to this value
	void SetAllStepSizes(double dStepSize);

	virtual void Iterate();

	// d should be a value between 0 and 1
	void SetChangeFactor(double d) { m_dChangeFactor = d; }
};



// At each iteration this algorithm moves in a random direction
// from the best point ever found. The size of the step is a
// random number raised to a constant power (called the
// conservativeness).
class GStochasticGreedySearch : public GRealVectorSearch
{
protected:
	double m_dRange;
	double m_dConservativeness;
	int m_nDimensions;
	double* m_pVector;
	double* m_pTest;
	double m_dError;

public:
	GStochasticGreedySearch(GRealVectorCritic* pCritic, double dMin, double dRange);
	virtual ~GStochasticGreedySearch();

	virtual void Iterate();

	// d should be greater than 1. A bigger value will cause it to usually
	// take small steps and only rarely take big steps. A smaller value
	// will cause it to take big steps more frequently.
	void SetConservativeness(double d) { m_dConservativeness = d; }
};




class GActionGreedySearch : public GActionPathSearch
{
protected:
	double m_dPrevError;
	GActionPath* m_pPath;

public:
	// Takes ownership of pStartState
	GActionGreedySearch(GActionPathState* pStartState, int nActionCount);
	virtual ~GActionGreedySearch();

	virtual bool Iterate();
	virtual GActionPath* GetBestPath();
	virtual double GetBestPathError();
#ifndef NO_TEST_CODE
	static void Test();
#endif // !NO_TEST_CODE
};



class GAStarSearch : public GActionPathSearch
{
protected:
	GAVLTree* m_pPriorityQueue;
	int m_nMaxPaths;
	double m_dBestError;
	GActionPath* m_pBestPath;

public:
	// Takes ownership of pStartState
	// nMaxPaths is the max number of unique paths to hold in the priority queue. When
	//		this number is exceeded, it throws out the worst paths. if nMaxPaths is small,
	//		the search resembles bar-search, except with a best-first ordering.
	GAStarSearch(GActionPathState* pStartState, int nActionCount, int nMaxPaths);
	virtual ~GAStarSearch();

	virtual bool Iterate();
	virtual GActionPath* GetBestPath();
	virtual double GetBestPathError();
#ifndef NO_TEST_CODE
	static void Test();
#endif // !NO_TEST_CODE
};



#endif // __GGREEDYSEARCH_H__