#include <ballistics.h>

Inheritance diagram for ballistics::Ballistics:

Public Member Functions
size_t	inputs () const override
	Number of inputs to a Brain.

size_t	outputs () const override
	Number of outputs from a Brain.

bool	evaluatePopulation (darwin::Population *population) const override
	Assigns fitness values to every genotype. More...

Public Member Functions inherited from darwin::Domain
virtual unique_ptr< core::PropertySet >	calibrateGenotype ([[maybe_unused]] const Genotype *genotype) const
	Optional: additional fitness metrics (normally not used in the population evaluation, ie a test set)

Detailed Description

A basic ballistics problem: output the angle required to hit a target at (x, y) coordinates. The magnitude of the initial velocity is fixed.

While seemingly simple, the analytical solution is not exactly trivial and it seems a good benchmark for Neuroevolution. The fitness function is:

1 - closest_distance / target_distance

An optional fitness bonus is added if the target is hit.

The inputs are simply the (x, y) target coordinates.

Input	Value
0	target x coordinate
1	target y coordinate

The single output indicates the aim angle

Output	Value
0	aim angle (radians)

Member Function Documentation

bool ballistics::Ballistics::evaluatePopulation ( darwin::Population * population ) const

overridevirtual

Assigns fitness values to every genotype.

Having a good fitness function is a key part of evolutionary algorithms:

Perhaps obvious, the fitness value should accurately estimate the quality of a particular solution
A "smooth" distribution is preferable since it provides a gradient which can guide the incremental search in the solutions space. (ex. if most fitness values are 1.0 or 0.0 it's hard to know which genotypes are good candidates for reproduction)

The documentation for this class was generated from the following files: