net.sf.tweety.math.examples.GradientDescentSolverEx Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of math Show documentation
There is a newer version: 1.6
/*
 *  This file is part of "TweetyProject", a collection of Java libraries for
 *  logical aspects of artificial intelligence and knowledge representation.
 *
 *  TweetyProject is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Lesser General Public License version 3 as
 *  published by the Free Software Foundation.
 *
 *  This program 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 Lesser General Public License for more details.
 *
 *  You should have received a copy of the GNU Lesser General Public License
 *  along with this program. If not, see .
 *
 *  Copyright 2020 The TweetyProject Team 
 */

package net.sf.tweety.math.examples;

import java.io.IOException;
import java.util.*;

import net.sf.tweety.commons.ParserException;
import net.sf.tweety.math.*;
import net.sf.tweety.math.opt.problem.ConstraintSatisfactionProblem;
import net.sf.tweety.math.opt.problem.OptimizationProblem;
import net.sf.tweety.math.opt.solver.BfgsSolver;
import net.sf.tweety.math.term.FloatConstant;
import net.sf.tweety.math.term.FloatVariable;
import net.sf.tweety.math.term.IntegerConstant;
import net.sf.tweety.math.term.Power;
import net.sf.tweety.math.term.Sum;
import net.sf.tweety.math.term.Term;
import net.sf.tweety.math.term.Variable;

/**
 * This class implements an example for the Gradient Descent Solver
 * @author Sebastian Franke
 */
public class GradientDescentSolverEx {

	public static ConstraintSatisfactionProblem createConstraintSatProb1() {
		FloatVariable m1 = new FloatVariable("Machine 1");
		FloatVariable m2 = new FloatVariable("Machine 2");
		//Target function = (m1+1)^2+m2^2
		Term opt = new Sum(new Power(new Sum(m1,new FloatConstant(1)), new IntegerConstant(2)), new Power(m2, new IntegerConstant(2)));

		
		
		OptimizationProblem prob = new OptimizationProblem(0);
		((OptimizationProblem)prob).setTargetFunction(opt);
		return prob;
		
	}
	

	public static void main(String[] args) throws ParserException, IOException, GeneralMathException{
		//Create toy problem
		ConstraintSatisfactionProblem prob = createConstraintSatProb1();
		Set constr = prob.getVariables();
		//Create starting point; all variables start at 0
		Map startingPoint = new HashMap();
		for(Variable x : constr) {
			startingPoint.put(x, new IntegerConstant(0));
		}
		//solve via Gradient Descent
		BfgsSolver solver = new BfgsSolver(startingPoint);
		Map solution = solver.solve(prob);
		System.out.println(solution.toString());
		
		
	}
}