An Analysis of the Influence of Non-effective Instructions in Linear Genetic Programming

2021 ◽  
pp. 1-23
Author(s):  
Léo Françoso Dal Piccol Sotto ◽  
Franz Rothlauf ◽  
Vinçcius Veloso de Melo ◽  
Márcio P. Basgalupp
Keyword(s):  
Genetic Programming ◽  
Directed Acyclic Graph ◽  
Genetic Material ◽  
Population Diversity ◽  
Search Performance ◽  
Linear Genetic Programming ◽  
Improve Performance ◽  
Neutral Mutations ◽  
Evolutionary Memory

Abstract Linear Genetic Programming (LGP) represents programs as sequences of instructions and has a Directed Acyclic Graph (DAG) dataflow. The results of instructions are stored in registers that can be used as arguments by other instructions. Instructions that are disconnected from the main part of the program are called non-effective instructions, or structural introns. They also appear in other DAG-based GP approaches like Cartesian Genetic Programming (CGP). This paper studies four hypotheses on the role of structural introns: non-effective instructions (1) serve as evolutionary memory, where evolved information is stored and later used in search, (2) preserve population diversity, (3) allow neutral search, where structural introns increase the number of neutral mutations and improve performance, and (4) serve as genetic material to enable program growth. We study different variants of LGP controlling the influence of introns for symbolic regression, classification, and digital circuits problems. We find that there is (1) evolved information in the non-effective instructions that can be reactivated and that (2) structural introns can promote programs with higher effective diversity. However, both effects have no influence on LGP search performance. On the other hand, allowing mutations to not only be applied to effective but also to noneffective instructions (3) increases the rate of neutral mutations and (4) contributes to program growth by making use of the genetic material available as structural introns. This comes along with a significant increase of LGP performance, which makes structural introns important for LGP.

scholarly journals Bias-variance decomposition in Genetic Programming

2016 ◽  
Vol 14 (1) ◽  
pp. 62-80 ◽  
Author(s):  
Taras Kowaliw ◽  
René Doursat
Keyword(s):  
Genetic Programming ◽  
Variance Decomposition ◽  
Initial Population ◽  
Linear Genetic Programming ◽  
Improve Performance ◽  
Training Samples ◽  
Bias Variance ◽  
Selection Of

AbstractWe study properties of Linear Genetic Programming (LGP) through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size, the initial population, and the function set used. We confirm and quantify several insights into the practical usage of GP, most notably that (a) the variance between runs is primarily due to initialization rather than the selection of training samples, (b) parameters can be reasonably optimized to obtain gains in efficacy, and (c) functions detrimental to evolvability are easily eliminated, while functions well-suited to the problem can greatly improve performance—therefore, larger and more diverse function sets are always preferable.

scholarly journals FMCGP: frameshift mutation cartesian genetic programming

2021 ◽  
Author(s):  
Wei Fang ◽  
Mindan Gu
Keyword(s):  
Genetic Programming ◽  
Frameshift Mutation ◽  
Population Diversity ◽  
Search Performance ◽  
Mutation Operator ◽  
Cartesian Genetic Programming ◽  
Dna Mutation ◽  
Regression Problems ◽  
The Individual ◽  
Acyclic Directed Graph

AbstractCartesian Genetic Programming (CGP) is a variant of Genetic Programming (GP) with the individuals represented by a two-dimensional acyclic directed graph, which can flexibly encode many computing structures. In general, CGP only uses a point mutation operator and the genotype of an individual is of fixed size, which may lead to the lack of population diversity and then cause the premature convergence. To address this problem in CGP, we propose a Frameshift Mutation Cartesian Genetic Programming (FMCGP), which is inspired by the DNA mutation mechanism in biology and the frameshift mutation caused by insertion or deletion of nodes is introduced to CGP. The individual in FMCGP has variable-length genotype and the proposed frameshift mutation operator helps to generate more diverse offspring individuals by changing the compiling framework of genotype. FMCGP is evaluated on the symbolic regression problems and Even-parity problems. Experimental results show that FMCGP does not exhibit the bloat problem and the use of frameshift mutation improves the search performance of the standard CGP.

scholarly journals Horizontal Gene Transfer Involving Chloroplasts

2021 ◽  
Vol 22 (9) ◽  
pp. 4484
Author(s):  
Ewa Filip ◽  
Lidia Skuza
Keyword(s):  
Gene Transfer ◽  
Horizontal Gene Transfer ◽  
Driving Force ◽  
Genetic Material ◽  
Adaptive Significance ◽  
Chloroplast Genomes ◽  
Organelle Genomes ◽  
Number Of Genes ◽  
Cellular Compartments

Horizontal gene transfer (HGT)- is defined as the acquisition of genetic material from another organism. However, recent findings indicate a possible role of HGT in the acquisition of traits with adaptive significance, suggesting that HGT is an important driving force in the evolution of eukaryotes as well as prokaryotes. It has been noted that, in eukaryotes, HGT is more prevalent than originally thought. Mitochondria and chloroplasts lost a large number of genes after their respective endosymbiotic events occurred. Even after this major content loss, organelle genomes still continue to lose their own genes. Many of these are subsequently acquired by intracellular gene transfer from the original plastid. The aim of our review was to elucidate the role of chloroplasts in the transfer of genes. This review also explores gene transfer involving mitochondrial and nuclear genomes, though recent studies indicate that chloroplast genomes are far more active in HGT as compared to these other two DNA-containing cellular compartments.

scholarly journals Sperm Cryopreservation in American Flamingo (Phoenicopterus Ruber): Influence of Cryoprotectants and Seminal Plasma Removal

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 203
Author(s):  
María Gemma Millán de la Blanca ◽  
Eva Martínez-Nevado ◽  
Cristina Castaño ◽  
Juncal García ◽  
Berenice Bernal ◽  
...  
Keyword(s):  
Seminal Plasma ◽  
Genetic Material ◽  
First Year ◽  
Sperm Cryopreservation ◽  
Straight Line ◽  
The Family ◽  
Second Year ◽  
American Flamingo ◽  
Phoenicopterus Ruber

The American flamingo is a useful model for the development of successful semen cryopreservation procedures to be applied to threatened related species from the family Phoenicopteridae, and to permit genetic material banking. Current study sought to develop effective sperm cryopreservation protocols through examining the influences of two permeating cryoprotectants and the seminal plasma removal. During two consecutive years (April), semen samples were collected and frozen from American flamingos. In the first year, the effect of two permeating cryoprotectants, DMA (dimethylacetamide) (6%) or Me2SO (dimethylsulphoxide) (8%), on frozen–thawed sperm variables were compared in 21 males. No differences were seen between DMA and Me2SO for sperm motility, sperm viability, and DNA fragmentation after thawing. In the second year, the role of seminal plasma on sperm cryoresistance was investigated in 31 flamingos. Sperm samples were cryopreserved with and without seminal plasma, using Me2SO (8%) as a cryoprotectant. The results showed that samples with seminal plasma had higher values than samples without seminal plasma for the following sperm variables: Straight line velocity (22.40 µm/s vs. 16.64 µm/s), wobble (75.83% vs. 69.40%), (p < 0.05), linearity (62.73% vs. 52.01%) and straightness (82.38% vs. 73.79%) (p < 0.01); but acrosome integrity was lower (55.56% vs. 66.88%) (p < 0.05). The cryoresistance ratio (CR) was greater in samples frozen with seminal plasma than without seminal plasma for CR-progressive motility (138.72 vs. 54.59), CR-curvilinear velocity (105.98 vs. 89.32), CR-straight line velocity (152.77 vs. 112.58), CR-average path velocity (122.48 vs. 98.12), CR-wobble (111.75 vs. 102.04) (p < 0.05), CR-linearity (139.41 vs. 113.18), and CR-straightness (124.02 vs. 109.97) (p < 0.01). This research demonstrated that there were not differences between Me2SO and DMA to successful freezing sperm of flamingos; seminal plasma removal did not provide a benefit for sperm cryopreservation.

Numerical analysis of the shear strength of circular reinforced concrete columns subjected to cyclic lateral loads using linear genetic programming

2020 ◽  
Vol 37 (7) ◽  
pp. 2517-2537
Author(s):  
Mostafa Rezvani Sharif ◽  
Seyed Mohammad Reza Sadri Tabaei Zavareh
Keyword(s):  
Numerical Modeling ◽  
Shear Strength ◽  
Reinforced Concrete ◽  
Numerical Analysis ◽  
Genetic Programming ◽  
Linear Genetic Programming ◽  
Rc Columns ◽  
Content Type ◽  
Alternative Approach ◽  
Engineering Problems

Purpose The shear strength of reinforced concrete (RC) columns under cyclic lateral loading is a crucial concern, particularly, in the seismic design of RC structures. Considering the costly procedure of testing methods for measuring the real value of the shear strength factor and the existence of several parameters impacting the system behavior, numerical modeling techniques have been very much appreciated by engineers and researchers. This study aims to propose a new model for estimation of the shear strength of cyclically loaded circular RC columns through a robust computational intelligence approach, namely, linear genetic programming (LGP). Design/methodology/approach LGP is a data-driven self-adaptive algorithm recently used for classification, pattern recognition and numerical modeling of engineering problems. A reliable database consisting of 64 experimental data is collected for the development of shear strength LGP models here. The obtained models are evaluated from both engineering and accuracy perspectives by means of several indicators and supplementary studies and the optimal model is presented for further purposes. Additionally, the capability of LGP is examined to be used as an alternative approach for the numerical analysis of engineering problems. Findings A new predictive model is proposed for the estimation of the shear strength of cyclically loaded circular RC columns using the LGP approach. To demonstrate the capability of the proposed model, the analysis results are compared to those obtained by some well-known models recommended in the existing literature. The results confirm the potential of the LGP approach for numerical analysis of engineering problems in addition to the fact that the obtained LGP model outperforms existing models in estimation and predictability. Originality/value This paper mainly represents the capability of the LGP approach as a robust alternative approach among existing analytical and numerical methods for modeling and analysis of relevant engineering approximation and estimation problems. The authors are confident that the shear strength model proposed can be used for design and pre-design aims. The authors also declare that they have no conflict of interest.

Choice and privatisation in Swedish primary care

2010 ◽  
Vol 6 (4) ◽  
pp. 549-569 ◽  
Author(s):  
Anders Anell
Keyword(s):  
Primary Care ◽  
Clinical Practice ◽  
Financial Incentives ◽  
Degrees Of Freedom ◽  
New Wave ◽  
Improve Performance ◽  
Financial Responsibility ◽  
New Models ◽  
Financial Characteristics

AbstractIn 2007, a new wave of local reforms involving choice for the population and privatisation of providers was initiated in Swedish primary care. Important objectives behind reforms were to strengthen the role of primary care and to improve performance in terms of access and responsiveness. The purpose of this article was to compare the characteristics of the new models and to discuss changes in financial incentives for providers and challenges regarding governance from the part of county councils. A majority of the models being introduced across the 21 county councils can best be described as innovative combinations between a comprehensive responsibility for providers and significant degrees of freedom regarding choice for the population. Key financial characteristics of fixed payment and comprehensive financial responsibility for providers may create financial incentives to under-provide care. Informed choices by the population, in combination with reasonably low barriers for providers to enter the primary care market, should theoretically counterbalance such incentives. To facilitate such competition is indeed a challenge, not only because of difficulties in implementing informed choices but also because the new models favour large and/or horizontally integrated providers. To prevent monopolistic behaviour, county councils may have to accept more competition as well as more governance over clinical practice than initially intended.

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