GradientDescentRootFinder (Tweety (Math) 1.16 API)

java.lang.Object
- net.sf.tweety.math.opt.RootFinder
- - net.sf.tweety.math.opt.OptimizationRootFinder
  - - net.sf.tweety.math.opt.GradientDescentRootFinder

```
public class GradientDescentRootFinder
extends OptimizationRootFinder
```
Implements the gradient descent method to find zeros of a (multi-dimensional) function.

Author:

Matthias Thimm

Field Summary

Fields
Modifier and Type Field Description

double precision
The precision of the approximation.
- Fields inherited from class net.sf.tweety.math.opt.RootFinder
  PRECISION

Constructor Summary

Constructors
Constructor	Description
`GradientDescentRootFinder(List<Term> functions, Map<Variable,Term> startingPoint)`	Creates a new root finder for the given starting point and the given (multi-dimensional) function
`GradientDescentRootFinder(Term function, Map<Variable,Term> startingPoint)`	Creates a new root finder for the given starting point and the given function

Method Summary

Modifier and Type Method Description

Map<Variable,Term> randomRoot()
Determines the values for the variables appearing in the function such the function evaluates to zero.
- Methods inherited from class net.sf.tweety.math.opt.OptimizationRootFinder
  buildOptimizationProblem
- Methods inherited from class net.sf.tweety.math.opt.RootFinder
  getFunctions, getStartingPoint, setStartingPoint
- Methods inherited from class java.lang.Object
  clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - precision
```
public double precision
```
    The precision of the approximation. The actual used precision depends on the number of variables.
- Constructor Detail
  - GradientDescentRootFinder
```
public GradientDescentRootFinder(Term function,
                                 Map<Variable,Term> startingPoint)
```
    Creates a new root finder for the given starting point and the given function
    
    Parameters:
    
    function - a function
    
    startingPoint - the starting point
  - GradientDescentRootFinder
```
public GradientDescentRootFinder(List<Term> functions,
                                 Map<Variable,Term> startingPoint)
```
    Creates a new root finder for the given starting point and the given (multi-dimensional) function
    
    Parameters:
    
    functions - a list of functions
    
    startingPoint - the starting point
- Method Detail
  - randomRoot
```
public Map<Variable,Term> randomRoot()
                                    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
    
    Returns:
    
    a map from variables to terms such that "function" evaluates to zero.
    
    Throws:
    
    GeneralMathException - if something went wrong.