# Computational Complexity, Genetic Programming, and Implications

@inproceedings{Rylander2001ComputationalCG, title={Computational Complexity, Genetic Programming, and Implications}, author={Bart Rylander and Terence Soule and James A. Foster}, booktitle={EuroGP}, year={2001} }

Recent theory work has shown that a Genetic Program (GP) used to produce programs may have output that is bounded above by the GP itself [1]. This paper presents proofs that show that 1) a program that is the output of a GP or any inductive process has complexity that can be bounded by the Kolmogorov complexity of the originating program; 2) this result does not hold if the random number generator used in the evolution is a true random source; and 3) an optimization problem being solved with a…

## 17 Citations

### Computational complexity and the genetic algorithm

- Computer Science
- 2001

A method for evaluating the complexity of a problem specifically for genetic algorithms is described, used to define two specific genetic algorithm complexity classes and the impact of quantum computers upon the complexity classes for evolutionary computation is examined.

### Quantum evolutionary programming

- Computer Science
- 2001

A simple quantum approach to genetic algorithms is presented and it is shown that in some cases, such as program induction, there is a measurable difference in quantum advantage of true randomness.

### Developing Automatic Synthesis Methodologies for Quantum Circuits using Genetic Algorithms Ph

- Computer Science
- 2004

The goal is to perform automatic quantum circuit synthesis for a given functional description using rippled steps, and the usage of a parser which will create an internal data structure for the provided description is proposed.

### Compression Genetic Algorithms and Quantum Genetic Algorithms

- Computer Science
- 2015

The approach of QGA is outlined by giving a comparison with Conventional Genetic Algorithm (CGA) to show that QGA can be a very promising tool for exploring search spaces.

### Implementing quantum genetic algorithms: a solution based on Grover's algorithm

- Computer ScienceCF '06
- 2006

It turns out that the genetic strategy is not particularly helpful in the quantum computation approach; therefore the solution consists of designing a special-purpose oracle that will work with a modified version of an already known algorithm (maximum finding [1]), in order to reduce the QGAs to a Grover search.

### Why We Do Not Evolve Software? Analysis of Evolutionary Algorithms

- Computer Science, BiologyEvolutionary bioinformatics online
- 2018

It is observed that nontrivial software from scratch and with no human intervention is not evolution from scratch, and computational complexity of the problem prevents it from being solved as currently attempted.

### Genetic Algorithms and Quantum Computation

- Computer ScienceArXiv
- 2004

A survey of the main works in GAs plus quantum computing including also the application of GAs for learning quantum operators and circuit design and quantum evolutionary programming is considered.

### Synthesis of Quantum Circuits Using Genetic Algorithm

- Computer Science
- 2009

The methodology of building a quantum circuit corresponding to a given quantum operation, expressed in terms of a unitary transform matrix, utilizing a specified quantum gate library has been proposed in this paper.

### Learning Causal Graph: A Genetic Programming Approach

- Computer Science
- 2014

An approach for learning causal graph based on Wiener-Granger causal-theory, with minor modifications, and use Genetic Programming to determine the parameters of Granger formula to show that SP500 has Granger-causal influence on NIKKE.

### Sobre expresiones cerradas para ondas gravitacionales

- Computer Science
- 2019

A new approach to find high-fidelity closed forms, ab-initio, without simplify the underlying model, in case of existence in the field of prediction and data analysis of complex systems, avoiding the curse of dimensionality is presented.

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