THE KOLMOGOROV METRIC AND A GENERALIZATION ON A CLASSIFICATION OF CELLULAR AUTOMATA

1994 ◽  
Vol 03 (03) ◽  
pp. 311-326 ◽  
Author(s):  
LOUIS D’ALOTTO ◽  
CHARLES GIARDINA
Keyword(s):  
Cellular Automata ◽  
Classification Approach ◽  
Generalized Metric ◽  
Kolmogorov Metric ◽  
Infinite Strings ◽  
Original Classification

This paper introduces and applies a new metric, on the space of bi-infinite strings (sequences), to the linear cellular automata classification approach of R. Gilman. The metric presented herein is a generalization of the metric used in the classification work of Gilman and it is shown that those original classification results also hold with this generalized metric.

To Understand the Informal (on the Book BY V. L. Tambovtsev “Economics of Informal Institutions”)

2015 ◽  
pp. 151-158
Author(s):  
A. Zaostrovtsev
Keyword(s):  
Social Psychology ◽  
Detailed Analysis ◽  
Human Behavior ◽  
Interdisciplinary Approach ◽  
Informal Institutions ◽  
Economic Thought ◽  
History Of ◽  
Original Classification

The review considers the first attempt in the history of Russian economic thought to give a detailed analysis of informal institutions (IF). It recognizes that in general it was successful: the reader gets acquainted with the original classification of institutions (including informal ones) and their genesis. According to the reviewer the best achievement of the author is his interdisciplinary approach to the study of problems and, moreover, his bias on the achievements of social psychology because the model of human behavior in the economic mainstream is rather primitive. The book makes evident that namely this model limits the ability of economists to analyze IF. The reviewer also shares the author’s position that in the analysis of the IF genesis the economists should highlight the uncertainty and reject economic determinism. Further discussion of IF is hardly possible without referring to this book.

scholarly journals Extensive Phylogenetic Analysis of Piscine Orthoreovirus Genomic Sequences Shows the Robustness of Subgenotype Classification

Pathogens ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 41
Author(s):  
Marcos Godoy ◽  
Daniel A. Medina ◽  
Rudy Suarez ◽  
Sandro Valenzuela ◽  
Jaime Romero ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Genetic Variation ◽  
Sequence Analysis ◽  
Molecular Phylogeny ◽  
Phylogenetic Trees ◽  
Genomic Segment ◽  
Double Stranded Rna ◽  
The Family ◽  
Original Classification

Piscine orthoreovirus (PRV) belongs to the family Reoviridae and has been described mainly in association with salmonid infections. The genome of PRV consists of about 23,600 bp, with 10 segments of double-stranded RNA, classified as small (S1 to S4), medium (M1, M2 and M3) and large (L1, L2 and L3); these range approximately from 1000 bp (segment S4) to 4000 bp (segment L1). How the genetic variation among PRV strains affects the virulence for salmonids is still poorly understood. The aim of this study was to describe the molecular phylogeny of PRV based on an extensive sequence analysis of the S1 and M2 segments of PRV available in the GenBank database to date (May 2020). The analysis was extended to include new PRV sequences for S1 and M2 segments. In addition, subgenotype classifications were assigned to previously published unclassified sequences. It was concluded that the phylogenetic trees are consistent with the original classification using the PRV genomic segment S1, which differentiates PRV into two major genotypes, I and II, and each of these into two subgenotypes, designated as Ia and Ib, and IIa and IIb, respectively. Moreover, some clusters of country- and host-specific PRV subgenotypes were observed in the subset of sequences used. This work strengthens the subgenotype classification of PRV based on the S1 segment and can be used to enhance research on the virulence of PRV.

scholarly journals Intelligent radar software defect classification approach based on the latent Dirichlet allocation topic model

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xi Liu ◽  
Yongfeng Yin ◽  
Haifeng Li ◽  
Jiabin Chen ◽  
Chang Liu ◽  
...  
Keyword(s):  
Latent Dirichlet Allocation ◽  
Topic Model ◽  
Recall Rate ◽  
Defect Classification ◽  
Software Defects ◽  
Classification Approach ◽  
Software Defect ◽  
Model Combining ◽  
Dirichlet Allocation

AbstractExisting software intelligent defect classification approaches do not consider radar characters and prior statistics information. Thus, when applying these appaoraches into radar software testing and validation, the precision rate and recall rate of defect classification are poor and have effect on the reuse effectiveness of software defects. To solve this problem, a new intelligent defect classification approach based on the latent Dirichlet allocation (LDA) topic model is proposed for radar software in this paper. The proposed approach includes the defect text segmentation algorithm based on the dictionary of radar domain, the modified LDA model combining radar software requirement, and the top acquisition and classification approach of radar software defect based on the modified LDA model. The proposed approach is applied on the typical radar software defects to validate the effectiveness and applicability. The application results illustrate that the prediction precison rate and recall rate of the poposed approach are improved up to 15 ~ 20% compared with the other defect classification approaches. Thus, the proposed approach can be applied in the segmentation and classification of radar software defects effectively to improve the identifying adequacy of the defects in radar software.

A Probabilistic Model for Diagnosing Misconceptions By The Pattern Classification Approach

1985 ◽  
Vol 10 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Kikumi K. Tatsuoka
Keyword(s):  
Artificial Intelligence ◽  
Item Response Theory ◽  
Item Response ◽  
Pattern Classification ◽  
Probabilistic Model ◽  
Probabilistic Approach ◽  
Response Patterns ◽  
Classification Approach ◽  
Response Errors

This paper introduces a probabilistic approach to the classification and diagnosis of erroneous rules of operations that result from misconceptions (“bugs”) in a procedural domain of arithmetic. The model is different from the usual deterministic strategies common in the field of artificial intelligence because variability of response errors is explicitly treated through item response theory. As a concrete example, we analyze a dataset that reflects the use of erroneous rules of operation in problems of signed-number subtraction. The same approach, however, is applicable to the classification of several different groups of response patterns caused by a variety of different underlying misconceptions, different backgrounds of knowledge, or treatment.

scholarly journals EVOLVING LOCALIZATIONS IN REACTION-DIFFUSION CELLULAR AUTOMATA

2008 ◽  
Vol 19 (04) ◽  
pp. 557-567 ◽  
Author(s):  
ANDREW ADAMATZKY ◽  
LARRY BULL ◽  
PIERRE COLLET ◽  
EMMANUEL SAPIN
Keyword(s):  
Cellular Automata ◽  
Chemical Species ◽  
Reaction Diffusion ◽  
Discrete Systems ◽  
Chemical Systems ◽  
Transition Functions ◽  
Phenomenological Studies ◽  
Spatially Extended ◽  
Limited Diffusion

We consider hexagonal cellular automata with immediate cell neighbourhood and three cell-states. Every cell calculates its next state depending on the integral representation of states in its neighbourhood, i.e., how many neighbours are in each one state. We employ evolutionary algorithms to breed local transition functions that support mobile localizations (gliders), and characterize sets of the functions selected in terms of quasi-chemical systems. Analysis of the set of functions evolved allows to speculate that mobile localizations are likely to emerge in the quasi-chemical systems with limited diffusion of one reagent, a small number of molecules are required for amplification of travelling localizations, and reactions leading to stationary localizations involve relatively equal amount of quasi-chemical species. Techniques developed can be applied in cascading signals in nature-inspired spatially extended computing devices, and phenomenological studies and classification of non-linear discrete systems.

Automatic Texture Based Classification of the Dynamics of One-Dimensional Binary Cellular Automata

2019 ◽  
Vol 8 (4) ◽  
pp. 41-61
Author(s):  
Marcelo Arbori Nogueira ◽  
Pedro Paulo Balbi de Oliveira
Keyword(s):  
Cellular Automata ◽  
Dynamic Behavior ◽  
Temporal Evolution ◽  
Computational Cost ◽  
Great Variability ◽  
Texture Descriptor ◽  
One Dimensional ◽  
Binary Images ◽  
Elementary Cellular Automata

Cellular automata present great variability in their temporal evolutions due to the number of rules and initial configurations. The possibility of automatically classifying its dynamic behavior would be of great value when studying properties of its dynamics. By counting on elementary cellular automata, and considering its temporal evolution as binary images, the authors created a texture descriptor of the images - based on the neighborhood configurations of the cells in temporal evolutions - so that it could be associated to each dynamic behavior class, following the scheme of Wolfram's classic classification. It was then possible to predict the class of rules of a temporal evolution of an elementary rule in a more effective way than others in the literature in terms of precision and computational cost. By applying the classifier to the larger neighborhood space containing 4 cells, accuracy decreased to just over 70%. However, the classifier is still able to provide some information about the dynamics of an unknown larger space with reduced computational cost.

Automorphissm Classification of Cellular Automata

2010 ◽  
Vol 104 (1-2) ◽  
pp. 125-140
Author(s):  
Hidenosuke Nishio
Keyword(s):  
Cellular Automata
Sign in / Sign up

Export Citation Format

Share Document