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Questions tagged [genetic-programming]

Genetic programming (GP) is a specialization of evolutionary computation where each individual is a computer program. It is used to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.

Genetic programming (GP) is a type of where each individual in a population is a computer program. It is used to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.

Traditional genetic programming, originally popularized by John Koza, represents code as expression trees, but this topic also includes other systems in which code evolves.

See also: , which refers to evolution-inspired algorithms in which an abstract representation of the solution is being evolved, rather than code itself.

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What is the difference between roulette wheel selection, rank selection and tournament selection?

I'm reading a slide about genetic programming, where some methods to select individuals, such as roulette wheel selection, rank selection and tournament selection, are mentioned. What is the difference between these three selection methods?
Trần Kim Dự
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Difference between exploration and exploitation in genetic algorithm

In evolutionary algorithms two main abilities maintained which are Exploration and Exploitation. In Exploration the algorithm searching for new solutions in new regions, while Exploitation means using already exist solutions and make refinement to…
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Binary Tournament Selection

My understanding of a tournament selection is: For a given tournament size, t , randomly select t individuals from the population and determine the winner of that tournament as the individual with the largest fitness function value. My question…
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Implementing crossover in genetic programming

I'm writing a genetic programming (GP) system (in C but that's a minor detail). I've read a lot of the literature (Koza, Poli, Langdon, Banzhaf, Brameier, et al) but there are some implementation details I've never seen explained. For example: I'm…
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Difference between Gene Expression Programming and Cartesian Genetic Programming

Something pretty annoying in evolutionary computing is that mildly different and overlapping concepts tend to pick dramatically different names. My latest confusion because of this is that gene-expression-programming seems very similar to…
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llvm based code mutation for genetic programming?

for a study on genetic programming, I would like to implement an evolutionary system on basis of llvm and apply code-mutations (possibly on IR level). I found llvm-mutate which is quite useful executing point mutations. As far as I have understood,…
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Are there programs that iteratively write new programs?

For about a year I have been thinking about writing a program that writes programs. This would primarily be a playful exercise that might teach me some new concepts. My inspiration came from negentropy and the ability for order to emerge from…
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How to get the parameters' type and return type of a function?

I'm trying to implement strong type genetic programming in python. Is there something like these sample? def funcA(a,b): return a + b return_type(funcA) output: and def funcA(a,b): return a + b parameter_type(funcA) output:…
user1065942
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How to fix premature convergence in simple GA (Python)?

Yesterday i started exploring the genetic algorithms, and when i ended up with some basic theory, i tried to write simple GA on Python, that solves Diophantine equation. I'm new to Python and GAs, so please, don't judge my code strictly. Problem I…
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Initial Genetic Programming Parameters

I did a little GP (note:very little) work in college and have been playing around with it recently. My question is in regards to the intial run settings (population size, number of generations, min/max depth of trees, min/max depth of initial trees,…
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Code bacteria: evolving mathematical behavior

It would not be my intention to put a link on my blog, but I don't have any other method to clarify what I really mean. The article is quite long, and it's in three parts (1,2,3), but if you are curious, it's worth the reading. A long time ago (5…
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Evolutionary Algorithms: Optimal Repopulation Breakdowns

It's really all in the title, but here's a breakdown for anyone who is interested in Evolutionary Algorithms: In an EA, the basic premise is that you randomly generate a certain number of organisms (which are really just sets of parameters), run…
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Genetic algorithms -- what are the benefits of sexual, as opposed to asexual, genetic algorithms?

Intuitively I'd think that if I want to find the "best" set of parameters, I can simply take the best performing 1 guy from a subset of lots of children, make that guy generate 100 children similar to himself, pick the best performer and repeat.…
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Genetic Programming - Fitness functions

Let's say I have a set of training examples where A_i is an attribute and the outcome is binary (yes or no): A1, A2, A3, Outcome red dark large yes green dark …
ale
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Optimal population size, mutate rate and mate rate in genetic algorithm

I have written a game playing program for a competition, which relies on some 16 floating point "constants". Changing a constant can and will have dramatic impact on playing style and success rate. I have also written a simple genetic algorithm to…
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