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Questions tagged [fitness-functions]

For questions related to fitness functions in the context of evolutionary computation and evolutionary algorithms. A fitness function is a function that assesses the quality (or fitness) of an individual (i.e. solution) in the population (in the case of population-based evolutionary algorithms).

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Can't the loss function be used as a fitness function?

Can't the loss function used in backpropagation be used as a fitness function in an evolutionary algorithm?
Display name's user avatar
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1 answer
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Best way to generate fitness landscape when using higher dimensional data

I'm using a GA to find the best set of parameters to maximize a fitness function. I want to draw a fitness landscape to visualize the effectiveness of the algorithm. The fitness function, calculated ...
program1232123's user avatar
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How to define a fitness function to make sure the best fitness value is 'close to 9' in genetic algorithm

I am learning about genetic algorithms (GA), but I encountered a question about the definition of the fitness function used in GA. I understand that the fitness function should return a scalar value (...
DavidK's user avatar
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1 answer
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Does pairing children with their parents cause any harm (in a genetic program)?

If you pair parents with their children (with a cross-over) does this prevent making individuals which are more fit or does this cause other side effects which are harmful to the genetic process? I ...
SandTh's user avatar
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0 answers
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How to calculate adjusted and normalized fitness when a higher raw fitness is better

I am reading Genetic Programming: On the Programming of Computers by Means of Natural Selection by John R. Koza. For calculating the "standardized fitness" of an individual, where a lower ...
Flux's user avatar
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1 vote
1 answer
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Is there a crossover that also considers that every index in the vector also influences the fitness function?

Is there a crossover that also considers that every index in the vector also influences the cost function? I have two vectors $v_1=[A_1, A_2, A_3, A_4, A_5]$ and $v_2=[A_5, A_3, A_2, A_1, A_4]$. The ...
MrPlanck's user avatar
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1 vote
1 answer
230 views

How to design fitness function for multiple objectives?

I am currently building a neural network with genetic algorithms that learns to fly a 2D drone to a target. My goal is that it achieves all tasks as fast as possible, but I want the drone to also fly ...
Rasmus's user avatar
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5 votes
3 answers
405 views

Does gradient descent in deep learning assume a smooth fitness landscape?

I've come across the concept of fitness landscape before and, in my understanding, a smooth fitness landscape is one where the algorithm can converge on the global optimum through incremental ...
Joebevo's user avatar
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1 answer
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Is it possible to optimize a multi-variable function with a reinforcement learning method?

I want to use RL instead of genetic or any other evolutionary algorithm in order to find the best parameter for a function. Here is the problem: Given a function $$f(x,y,z, \text{data}),$$ where $x$, $...
Arta Asadi's user avatar
1 vote
1 answer
619 views

How to deal with evolutionary/genetic fitness function that can have both negative and positive values?

I am optimising function that can have both positive and negative values in pretty much unknown ranges, might be -100, 30, 0.001, or 4000, or -0.4 and I wonder how I can transform these results so I ...
GKozinski's user avatar
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1 answer
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How to design a fitness function for a problem where there are 2 objectives?

I am told to express a fitness function for a question I have been presented. I am unsure how I would express the function. In words, what I have written down makes sense but turning this into a ...
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1 vote
0 answers
239 views

How can I perform the forward pass in a neural network evolved with NEAT, given that some connections may not exist or there may be loopy connections?

I have a problem that arose as part of a NEAT (Neuro Evolution Through Augmenting Topologies) implementation that I am writing. I am wanting it to produce topologies or graphs that describe neural ...
Rohan Asokan's user avatar
3 votes
2 answers
475 views

Is it possible to perform neuroevolution without a fitness function?

My question is about neuroevolution (genetic algorithm + neural network): I want to create artificial life by evolving agents. But instead of relying on a fitness function, I would like to have the ...
LU15.W1R7H's user avatar
4 votes
0 answers
769 views

How to perform classification with NEAT-Python?

I am trying to do classification using NEAT-python for the first time, and I am having difficulty getting the accuracy rate. I tried the same problem with an ANN and was able to get a good accuracy ...
Linkuz's user avatar
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3 votes
1 answer
209 views

Is there any disadvantage of the maximum number of fitness function call as a stop criterion?

I'm studying different stop criteria in genetic algorithms and the advantages and disadvantages of each of them for evaluating different algorithms. One of these methods is the max number of fitness ...
helen's user avatar
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2 votes
0 answers
62 views

Is a neural network the correct approach to optimising a fitness function in a genetic algorithm?

I've written an application to help players pick the optimal heroes during the draft phase of the Heroes of the Storm MOBA. It can be daunting to pick from 80+ characters that have synergies/counters ...
Richard Nienaber's user avatar
3 votes
2 answers
6k views

How to design a fitness function for the 8-queens problem?

In evolutionary computation and, in particular, in the context of genetic algorithms, there is the concept of a fitness function. The better a state, the greater the value of the fitness function for ...
Huma Qaseem's user avatar
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2 answers
9k views

How to create a good fitness function?

In genetic algorithms, a function called "fitness" (or "evaluation") function is used to determine the "fitness" of the chromosomes. Creating a good fitness function is one of the challenging tasks in ...
Abbas Ali's user avatar
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2 votes
1 answer
281 views

How can a genetic algorithm adapt and get better in a changing environment?

I've just started studying genetic algorithms and I'm not able to understand why a genetic algorithm can improve if, at each learning, the 'world' that the population encounters change. For example, ...
Giorgio Labate's user avatar
2 votes
1 answer
392 views

Fitness function in genetic algorithm based on an interval

I am writing an app, where when a ball is shot from a canon it is supposed to land in a hole that is on a given distance. The ball is supposed to land between the distance of the beginning of the hole ...
ivaa14's user avatar
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6 votes
2 answers
287 views

Why does the fitness of my neural network to play tic-tac-toe keep oscillating?

I wrote a simple feed-forward neural network that plays tic-tac-toe: 9 neurons in input layers: 1 - my sign, -1 - opponent's sign, 0 - empty; 9 neurons in hidden layer: value calculated using ReLU; 9 ...
Perpetuum's user avatar
4 votes
1 answer
124 views

Can I compute the fitness of an agent based on a low number of runs of the game?

I'm developing an AI to play a card game with a genetic algorithm. Initially, I will evaluate it against a player that plays randomly, so there will naturally be a lot of variance in the results. I ...
OrangeMan's user avatar
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1 vote
1 answer
588 views

How can I calculate the "mean best fitness" measure in genetic algorithms?

I've just started to learn genetic algorithms and I have found these measurements of runs that I don't understand: MBF: The mean best fitness measure (MBF) is the average of the best fitness values ...
VansFannel's user avatar
3 votes
1 answer
141 views

How do I design a fitness function that weighs the importance of eating food?

Summary: I am teaching bots to pick food on a playing field. Some food is poisonous and some is good. Food Details: Poisonous food subtracts score points and good food adds. Food points vary based on ...
Alexus's user avatar
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3 votes
2 answers
854 views

How does adjusted fitness penalize large species in NEAT?

I'm learning about NEAT from the paper Evolving Neural Networks through Augmenting Topologies. I'm having trouble understanding how adjusted fitness penalizes large species and prevents them from ...
wonder's user avatar
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4 votes
1 answer
515 views

How do I use a genetic algorithm to generate the scores of an evaluation function for alpha-beta pruning?

I have created a Gomoku (5 in a row) AI using Alpha-Beta Pruning. It makes moves on a not-so-stupid level. First, let me vaguely describe the evaluation function of the Alpha-Beta algorithm. When it ...
Dashadower's user avatar
4 votes
1 answer
1k views

What is an appropriate fitness function for a simulated self-driving car?

I have been working for ages on a neuro-evolution AI program, where cars learn how to race around a track. Presently, I have a rudimentary fitness function that awards points for every degree ...
Aniekan Umoren's user avatar
4 votes
1 answer
234 views

How to improve the performance of my model trained with NEAT for a drone to learn how to fly?

I am working on a project in which a drone needs to learn how to fly. I am using NEAT. For the first experiment, I want the drone to learn how to hover inside a $3 \times 3 \times 3$ meters box. My ...
smallbit's user avatar
1 vote
1 answer
255 views

Is my understanding of confidence (precision) correct?

I'm attempting to develop a genetic algorithm capable of discovering classification rules for a given data set, a number of papers make use of the confidence (precision) and coverage of a rule to ...
Astronought's user avatar