C# 클래스 SharpNeat.Core.EvaluationInfo

Encapsulates genome evaluation data; specifically whether the genome has been evaluated, the genome's fitness, how many times the genome has been evaluated and if more than once then the mean fitness. Mean fitness is sometimes used when evaluations are non-determininstic (where each evaluation with the same parameters results in a different fitness, usually following some distribution curve) or else successive evaluations use different evaluation parameters and therefore result in different fitnesses. This approach is sometimes used in order to evaluate against a very computationally expensive fitness scheme, or indeed a computationally intractable scheme - i.e. we only execute against some subset of the problem space for each genome evaluation, and thus we obtain a more representative value for a genome's fitness by averaging over successive evaluations.
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공개 메소드들

메소드 설명
EvaluationInfo ( int fitnessHistoryLength ) : System

Construct and allocate the specified amount of memory for fitness history. Use zero if you don't require fitness history - but note that no arithmetic mean will be available.

IncrEvaluationPassCount ( ) : void

Increments EvaluationPassCount.

SetFitness ( double fitness ) : void

Assign a fitness. If a fitness history buffer was created then the value will be enqueued in the buffer.

메소드 상세

EvaluationInfo() 공개 메소드

Construct and allocate the specified amount of memory for fitness history. Use zero if you don't require fitness history - but note that no arithmetic mean will be available.
public EvaluationInfo ( int fitnessHistoryLength ) : System
fitnessHistoryLength int
리턴 System

IncrEvaluationPassCount() 공개 메소드

Increments EvaluationPassCount.
public IncrEvaluationPassCount ( ) : void
리턴 void

SetFitness() 공개 메소드

Assign a fitness. If a fitness history buffer was created then the value will be enqueued in the buffer.
public SetFitness ( double fitness ) : void
fitness double
리턴 void