PROPERTIES OF SELF-REPLICATING CELLULAR AUTOMATA SYSTEMS DISCOVERED USING GENETIC PROGRAMMING

2007 ◽  
Vol 10 (supp01) ◽  
pp. 61-84 ◽  
Author(s):  
ZHIJIAN PAN ◽  
JAMES REGGIA ◽  
DONGHONG GAO
Keyword(s):  
Cellular Automata ◽  
Genetic Programming ◽  
A Priori ◽  
Computation Time ◽  
Initial Configuration ◽  
Number Of Components ◽  
Arbitrary Structure ◽  
Wide Range ◽  
State Changes ◽  
Self Replication

We recently formulated an approach to representing structures in cellular automata (CA) spaces, and the rules that govern cell state changes, that is amenable to manipulation by genetic programming (GP). Using this approach, it is possible to efficiently generate self-replicating configurations for fairly arbitrary initial structures. Here, we investigate the properties of self-replicating systems produced using GP in this fashion as the initial configuration's size, shape, symmetry, allowable states, and other factors are systematically varied. We find that the number of GP generations, computation time, and number of resulting rules required by an arbitrary structure to self-replicate are positively and jointly correlated with the number of components, configuration shape, and allowable states in the initial configuration, but inversely correlated with the presence of repeated components, repeated sub-structures, and/or symmetric sub-structures. We conclude that GP can be used as a "replicator factory" to produce a wide range of self-replicating CA configurations, and that the properties of the resulting replicators can be predicted in part a priori. The rules controlling self-replication that are created by GP generally differ from those created manually in past CA studies.

Computational Discovery of Instructionless Self-Replicating Structures in Cellular Automata

2010 ◽  
Vol 16 (1) ◽  
pp. 39-63 ◽  
Author(s):  
Zhijian Pan ◽  
James A. Reggia
Keyword(s):  
Information Processing ◽  
Cellular Automata ◽  
Genetic Programming ◽  
Secondary Structures ◽  
Computational Discovery ◽  
Processing Properties ◽  
The Given ◽  
Self Replication ◽  
Instruction Sequence

Cellular automata models have historically been a major approach to studying the information-processing properties of self-replication. Here we explore the feasibility of adopting genetic programming so that, when it is given a fairly arbitrary initial cellular automata configuration, it will automatically generate a set of rules that make the given configuration replicate. We found that this approach works surprisingly effectively for structures as large as 50 components or more. The replication mechanisms discovered by genetic programming work quite differently than those of many past manually designed replicators: There is no identifiable instruction sequence or construction arm, the replicating structures generally translate and rotate as they reproduce, and they divide via a fissionlike process that involves highly parallel operations. This makes replication very fast, and one cannot identify which descendant is the parent and which is the child. The ability to automatically generate self-replicating structures in this fashion allowed us to examine the resulting replicators as their properties were systematically varied. Further, it proved possible to produce replicators that simultaneously deposited secondary structures while replicating, as in some past manually designed models. We conclude that genetic programming is a powerful tool for studying self-replication that might also be profitably used in contexts other than cellular spaces.

Transient electromagnetic inversion based on an approximate solution to the forward problem

Geophysics ◽  
1988 ◽  
Vol 53 (1) ◽  
pp. 118-128 ◽  
Author(s):  
Mark M. Goldman
Keyword(s):  
Objective Function ◽  
A Priori ◽  
Computation Time ◽  
Real Data ◽  
Equivalence Problem ◽  
Maximum Relative Error ◽  
Desktop Computer ◽  
Forward Algorithm ◽  
Transient Electromagnetic ◽  
Wide Range

A rapid algorithm for forward one‐dimensional modeling is based on the graphical construction of a multi‐layered apparent resistivity curve using an appropriate combination of two‐layered curves. A collection of two‐layered curves is calculated only once for fixed geoelectrical parameters and saved for future use; an arbitrary two‐layered curve within the wide range of the geoelectrical parameters is then obtained by simple interpolation. This method reduces computation time over other fast algorithms by at least one order of magnitude; in addition, it does not produce any significant computation errors in the late stage as do most other methods. A maximum relative error of about 10 to 15 percent may occur at a few points (usually two to three) in the vicinity of the intersection of the two‐layered curves. In most cases, however, this error does not affect the inversion since the relative contributions of these points to an objective function are small. The application of such a rapid forward algorithm allows one to attack the equivalence problem. For this purpose, several starting search points are randomly distributed within a feasible range in the parameter space. The inversion is then begun with the initial guesses for the parameters; several if not all of the minima of the objective function are found within the specified parameter range. To reduce ambiguity of the interpretation, all reasonable solutions are then correlated with available a priori geologic and/or geophysical information. Application of the above technique to real data shows the ability of the algorithm to detect equivalence and, thus, render the interpretation more objective. Both forward and inverse programs have been installed on a portable desktop computer (an IBM-PC compatible). The programs are easy to use and allow interpretation to be carried out in the field.

Simulating Self-Regeneration and Self-Replication Processes Using Movable Cellular Automata with a Mutual Equilibrium Neighborhood

2020 ◽  
Vol 29 (4) ◽  
pp. 741-757
Author(s):  
Kateryna Hazdiuk ◽  
◽  
Volodymyr Zhikharevich ◽  
Serhiy Ostapov ◽  
◽  
...  
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Three Dimensional ◽  
Computer Models ◽  
The Self ◽  
Model Construction ◽  
Natural Phenomena ◽  
Different Types ◽  
Movable Cellular Automata ◽  
Self Replication

This paper deals with the issue of model construction of the self-regeneration and self-replication processes using movable cellular automata (MCAs). The rules of cellular automaton (CA) interactions are found according to the concept of equilibrium neighborhood. The method is implemented by establishing these rules between different types of cellular automata (CAs). Several models for two- and three-dimensional cases are described, which depict both stable and unstable structures. As a result, computer models imitating such natural phenomena as self-replication and self-regeneration are obtained and graphically presented.

scholarly journals A Systematic Review and Qualitative Synthesis Resulting in a Typology of Elementary Classroom Movement Integration Interventions

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Spyridoula Vazou ◽  
Collin A. Webster ◽  
Gregory Stewart ◽  
Priscila Candal ◽  
Cate A. Egan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Teacher Collaboration ◽  
A Priori ◽  
Real Life ◽  
Dose Intensity ◽  
Routine Practice ◽  
Qualitative Synthesis ◽  
Wide Range ◽  
Meta Analyses ◽  
Movement Integration

Abstract Background/Objective Movement integration (MI) involves infusing physical activity into normal classroom time. A wide range of MI interventions have succeeded in increasing children’s participation in physical activity. However, no previous research has attempted to unpack the various MI intervention approaches. Therefore, this study aimed to systematically review, qualitatively analyze, and develop a typology of MI interventions conducted in primary/elementary school settings. Subjects/Methods Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to identify published MI interventions. Irrelevant records were removed first by title, then by abstract, and finally by full texts of articles, resulting in 72 studies being retained for qualitative analysis. A deductive approach, using previous MI research as an a priori analytic framework, alongside inductive techniques were used to analyze the data. Results Four types of MI interventions were identified and labeled based on their design: student-driven, teacher-driven, researcher-teacher collaboration, and researcher-driven. Each type was further refined based on the MI strategies (movement breaks, active lessons, other: opening activity, transitions, reward, awareness), the level of intrapersonal and institutional support (training, resources), and the delivery (dose, intensity, type, fidelity). Nearly half of the interventions were researcher-driven, which may undermine the sustainability of MI as a routine practice by teachers in schools. An imbalance is evident on the MI strategies, with transitions, opening and awareness activities, and rewards being limitedly studied. Delivery should be further examined with a strong focus on reporting fidelity. Conclusions There are distinct approaches that are most often employed to promote the use of MI and these approaches may often lack a minimum standard for reporting MI intervention details. This typology may be useful to effectively translate the evidence into practice in real-life settings to better understand and study MI interventions.

Applications of 3D printing in critical care medicine: A scoping review

2021 ◽  
pp. 0310057X2097665
Author(s):  
Natasha Abeysekera ◽  
Kirsty A Whitmore ◽  
Ashvini Abeysekera ◽  
George Pang ◽  
Kevin B Laupland
Keyword(s):  
Critical Care ◽  
Scoping Review ◽  
A Priori ◽  
Three Dimensional ◽  
Critical Care Medicine ◽  
Future Research ◽  
Care Practice ◽  
Three Dimensional Printing ◽  
Wide Range ◽  
Dimensional Printing

Although a wide range of medical applications for three-dimensional printing technology have been recognised, little has been described about its utility in critical care medicine. The aim of this review was to identify three-dimensional printing applications related to critical care practice. A scoping review of the literature was conducted via a systematic search of three databases. A priori specified themes included airway management, procedural support, and simulation and medical education. The search identified 1544 articles, of which 65 were included. Ranging across many applications, most were published since 2016 in non – critical care discipline-specific journals. Most studies related to the application of three-dimensional printed models of simulation and reported good fidelity; however, several studies reported that the models poorly represented human tissue characteristics. Randomised controlled trials found some models were equivalent to commercial airway-related skills trainers. Several studies relating to the use of three-dimensional printing model simulations for spinal and neuraxial procedures reported a high degree of realism, including ultrasonography applications three-dimensional printing technologies. This scoping review identified several novel applications for three-dimensional printing in critical care medicine. Three-dimensional printing technologies have been under-utilised in critical care and provide opportunities for future research.

scholarly journals Hierarchical Matching and Regression with Application to Photometric Redshift Estimation

2016 ◽  
Vol 12 (S325) ◽  
pp. 145-155
Author(s):  
Fionn Murtagh
Keyword(s):  
Information Structure ◽  
Data Analytics ◽  
A Priori ◽  
Sloan Digital Sky Survey ◽  
Photometric Redshifts ◽  
Merging Galaxies ◽  
Photometric Redshift ◽  
Sky Survey ◽  
Wide Range ◽  
Regression Problems

AbstractThis work emphasizes that heterogeneity, diversity, discontinuity, and discreteness in data is to be exploited in classification and regression problems. A global a priori model may not be desirable. For data analytics in cosmology, this is motivated by the variety of cosmological objects such as elliptical, spiral, active, and merging galaxies at a wide range of redshifts. Our aim is matching and similarity-based analytics that takes account of discrete relationships in the data. The information structure of the data is represented by a hierarchy or tree where the branch structure, rather than just the proximity, is important. The representation is related to p-adic number theory. The clustering or binning of the data values, related to the precision of the measurements, has a central role in this methodology. If used for regression, our approach is a method of cluster-wise regression, generalizing nearest neighbour regression. Both to exemplify this analytics approach, and to demonstrate computational benefits, we address the well-known photometric redshift or ‘photo-z’ problem, seeking to match Sloan Digital Sky Survey (SDSS) spectroscopic and photometric redshifts.

scholarly journals A Consistent Track-to-Track Fusion Method Based on Copula Theory

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Kelin Lu ◽  
K. C. Chang ◽  
Rui Zhou
Keyword(s):  
Probability Distributions ◽  
A Priori ◽  
Joint Probability ◽  
Network Connectivity ◽  
Consistent Estimate ◽  
Fusion Algorithm ◽  
Copula Theory ◽  
Wide Range ◽  
Primary Advantage ◽  
Joint Probability Distributions

This paper addresses the problem of distributed fusion when the conditional independence assumptions on sensor measurements or local estimates are not met. A new data fusion algorithm called Copula fusion is presented. The proposed method is grounded on Copula statistical modeling and Bayesian analysis. The primary advantage of the Copula-based methodology is that it could reveal the unknown correlation that allows one to build joint probability distributions with potentially arbitrary underlying marginals and a desired intermodal dependence. The proposed fusion algorithm requires no a priori knowledge of communications patterns or network connectivity. The simulation results show that the Copula fusion brings a consistent estimate for a wide range of process noises.

scholarly journals ON DIVERSITY OF CONFIGURATIONS GENERATED BY EXCITABLE CELLULAR AUTOMATA WITH DYNAMICAL EXCITATION INTERVALS

2012 ◽  
Vol 23 (12) ◽  
pp. 1250085 ◽  
Author(s):  
ANDREW ADAMATZKY
Keyword(s):  
Cellular Automata ◽  
Lower Boundary ◽  
Morphological Diversity ◽  
Excitable Media ◽  
Stationary Waves ◽  
Future Studies ◽  
Time Dynamics ◽  
Wide Range ◽  
Localized Excitations ◽  
Upper Boundary

Excitable cellular automata with dynamical excitation interval exhibit a wide range of space-time dynamics based on an interplay between propagating excitation patterns which modify excitability of the automaton cells. Such interactions leads to formation of standing domains of excitation, stationary waves and localized excitations. We analyzed morphological and generative diversities of the functions studied and characterized the functions with highest values of the diversities. Amongst other intriguing discoveries we found that upper boundary of excitation interval more significantly affects morphological diversity of configurations generated than lower boundary of the interval does and there is no match between functions which produce configurations of excitation with highest morphological diversity and configurations of interval boundaries with highest morphological diversity. Potential directions of future studies of excitable media with dynamically changing excitability may focus on relations of the automaton model with living excitable media, e.g. neural tissue and muscles, novel materials with memristive properties and networks of conductive polymers.

Data-Driven Analysis of Engine Mission Severity Using Non-Dimensional Groups

2021 ◽  
Author(s):  
Tim Brandes ◽  
Stefano Scarso ◽  
Christian Koch ◽  
Stephan Staudacher
Keyword(s):  
Support Vector Machine ◽  
Computation Time ◽  
Principal Component ◽  
General Term ◽  
Support Vector ◽  
Physical Parameters ◽  
Machine Model ◽  
Precision Error ◽  
Operational Conditions ◽  
Wide Range

Abstract A numerical experiment of intentionally reduced complexity is used to demonstrate a method to classify flight missions in terms of the operational severity experienced by the engines. In this proof of concept, the general term of severity is limited to the erosion of the core flow compressor blade and vane leading edges. A Monte Carlo simulation of varying operational conditions generates a required database of 10000 flight missions. Each flight is sampled at a rate of 1 Hz. Eleven measurable or synthesizable physical parameters are deemed to be relevant for the problem. They are reduced to seven universal non-dimensional groups which are averaged for each flight. The application of principal component analysis allows a further reduction to three principal components. They are used to run a support-vector machine model in order to classify the flights. A linear kernel function is chosen for the support-vector machine due to its low computation time compared to other functions. The robustness of the classification approach against measurement precision error is evaluated. In addition, a minimum number of flights required for training and a sensible number of severity classes are documented. Furthermore, the importance to train the algorithms on a sufficiently wide range of operations is presented.

Simulation of microstructure evolution during recrystallization using a high resolution three dimensional cellular automaton

2004 ◽  
Vol 120 ◽  
pp. 225-230
Author(s):  
P. Mukhopadhyay ◽  
M. Loeck ◽  
G. Gottstein
Keyword(s):  
High Resolution ◽  
Cellular Automata ◽  
Cellular Automaton ◽  
Microstructure Evolution ◽  
Static Recrystallization ◽  
Three Dimensional ◽  
Computation Time ◽  
Recrystallization Process ◽  
Recovery Condition ◽  
Physically Based

A more refined 3D cellular Automata (CA) algorithm has been developed which has increased the resolution of the space and reduced the computation time and can take care of the complexity of recrystallization process through physically based solutions. This model includes recovery, condition for nucleation and orientation dependent variable nuclei growth as a process of primary static recrystallization. Incorporation of microchemistry effects makes this model suitable for simulating recrystallization behaviour in terms of texture, kinetics and microstructure of different alloys. The model is flexible to couple up with other simulation programs on a common database.

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