Package org.tweetyproject.math.opt.rootFinder

Class HessianGradientDescentRootFinder

java.lang.Object

org.tweetyproject.math.opt.rootFinder.RootFinder

org.tweetyproject.math.opt.rootFinder.OptimizationRootFinder

org.tweetyproject.math.opt.rootFinder.HessianGradientDescentRootFinder

public class HessianGradientDescentRootFinder
extends OptimizationRootFinder

Implements the hessiane/gradient descent method to find zeros of a (multi-dimensional) function.

Author:

Matthias Thimm

Field Summary

Fields inherited from class org.tweetyproject.math.opt.rootFinder.RootFinder

PRECISION

Constructor Summary

Constructors

Constructor	Description
HessianGradientDescentRootFinder()	Creates a new root finder for the given starting point and the given (multi-dimensional) function

Method Summary

Modifier and Type	Method	Description
Map<Variable,Term>	randomRoot(List<Term> functions, Map<Variable,Term> startingPoint)	Determines the values for the variables appearing in the function such the function evaluates to zero.

Methods inherited from class org.tweetyproject.math.opt.rootFinder.RootFinder

getFunctions, getStartingPoint, setStartingPoint

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

HessianGradientDescentRootFinder

public HessianGradientDescentRootFinder()

Creates a new root finder for the given starting point and the given (multi-dimensional) function

Method Details

randomRoot

public Map<Variable,Term> randomRoot(List<Term> functions,
 Map<Variable,Term> startingPoint)
                              throws GeneralMathException

Description copied from class: RootFinder

Determines the values for the variables appearing in the function such the function evaluates to zero.

Specified by:

randomRoot in class OptimizationRootFinder

Parameters:

functions - the functions

startingPoint - the starting point for the search

Returns:

a map from variables to terms such that "function" evaluates to zero.

Throws:

GeneralMathException - if something went wrong.