Thesis (M. Sc.)--Carleton University, 1997. / Includes bibliographical references. Also available in electronic format on the Internet.

Τα κυψελικά αυτόματα (ΚΑ) αποτελούν την εξιδανίκευση ενός φυσικού συστήματος όπου ο χώρος και ο χρόνος είναι διακριτοί και οι φυσικές ποσότητες λαμβάνουν μόνο ένα πεπερασμένο σύνολο τιμών. Τα κυψελικά αυτόματα αποτελούνται από ένα πλέγμα με διακριτούς πανομοιότυπους κόμβους. Κάθε σημείο-κόμβος του πλέγματος χαρακτηρίζεται από μία τιμή η οποία δεν είναι αυθαίρετη, αλλά λαμβάνεται από ένα συγκεκριμένο σύνολο ‘επιτρεπτών’ ακέραιων τιμών. Οι τιμές αυτών των κόμβων του πλέγματος εξελίσσονται από τη μία χρονική στιγμή στην άλλη σύμφωνα με προκαθορισμένους τοπικούς κανόνες. Η συνολική δομή αποτελεί ένα μοντέλο παράλληλου υπολογισμού. ΄Οταν η απλή δομή του μοντέλου επαναλαμβάνεται, προκύπτουν πολύπλοκα πρότυπα που μπορούν να προσομοιώσουν ποικίλα πολύπλοκα φυσικά φαινόμενα και συστήματα. Χρησιμοποιούμε τα κυψελικά αυτόματα για να προσομοιώσουμε έναν αλγόριθμο ελέγχου τοπολογίας για ασύρματα δίκτυα αισθητήρων. Τα ασύρματα δίκτυα αισθητήρων αποτελούνται από ένα μεγάλο αριθμό διασκορπισμένων αισθητήρων-κόμβων που λειτουργούν με μπαταρίες. Σκοπός του προβλήματος ελέγχου τοπολογίας σε ασύρματα δίκτυα αισθητήρων είναι η επιλογή κατάλληλου υποσυνόλου κόμβων ικανών να παρακολουθούν μια περιοχή με στόχο τη μικρότερη δυνατή κατανάλωση ενέργειας και ως εκ τούτου την επέκταση της διάρκειας ζωής του δικτύου. / Cellular automata (CA) are an idealization of a physical system where space and time are discrete and the physical quantities take only a finite set of values. Cellular automata consist of a regular grid of identical cells-nodes. Each node is characterized by a non arbitrary value selected by a specific set of appropriate integers. The values of the nodes change over time according to predefined localized rules. The overall structure can be viewed as a parallel processing device. This simple structure when iterated several times produces complex patterns displaying the potential to simulate different sophisticated natural phenomena. We use cellular automata for simulating a topology control algorithm in Wireless Sensor Networks (WSNs). WSNs are composed of a large number of distributed sensor nodes operating on batteries; the objective of the topology control problem in WSNs is to select an appropriate subset of nodes able to monitor a region at a minimum energy consumption cost thus extending the network lifetime.

CARNEIRO, Lílian de Oliveira. Simulação de evacuação de multidão por autômato celular - Estudo de caso em um estádio de futebol. 2012. 76 f. Dissertação (Mestrado em ciência da computação)- Universidade Federal do Ceará, Fortaleza-CE, 2012. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-07-11T18:00:03Z No. of bitstreams: 1 2012_dis_locarneiro.pdf: 2162310 bytes, checksum: b6478d286f97bf68667c0ab9086d7fb6 (MD5) / Approved for entry into archive by Rocilda Sales (rocilda@ufc.br) on 2016-07-18T16:03:57Z (GMT) No. of bitstreams: 1 2012_dis_locarneiro.pdf: 2162310 bytes, checksum: b6478d286f97bf68667c0ab9086d7fb6 (MD5) / Made available in DSpace on 2016-07-18T16:03:57Z (GMT). No. of bitstreams: 1 2012_dis_locarneiro.pdf: 2162310 bytes, checksum: b6478d286f97bf68667c0ab9086d7fb6 (MD5) Previous issue date: 2012 / The evacuation from crowded places, subjected to physical and temporal restrictions, is a matter that deserves special attention. If a crowd fails to escape in time from a hazardous environment, by taking a wrong way or by selecting a bad exit, there is great risk of injuries and death. Simulations of crowd evacuation are very important to try to minimize those types of risk. However, trying to simulate emergency situations in real environments is either very expensive or even impossible. Therefore, computer simulation of crowd evacuation is a better alternative. The soccer stadiums are examples of environments that may present risk to people's lives in case of emergency evacuation. The main objective of this work is to gain understanding of the inherent aspects of the problem of emergency evacuation simulation, and to investigate the dynamics of the evacuation behavior of crowds during an emergency evacuation from a soccer stadium. For this, it was proposed a new model for crowd evacuation based on the cellular automata model. In order to validate the proposed model, tests in different situations were performed. It was shown that the proposed model is able to simulate the evacuation of complex environments in an efficient way. / A evacuação de locais aglomerados, sujeita a restrições físicas e temporais, é uma questão que merece atenção especial. Se uma multidão falha ao escapar em tempo de um ambiente perigoso, por tomar um caminho errado ou por escolher uma saída ruim, há um grande risco de lesões e morte. Simulações de evacuação de multidão são muito importantes para tentar minimizar esses tipos de riscos. Porém, tentar simular situações de emergência em ambientes reais ou é muito caro ou mesmo impossível. Portanto, a simulação da evacuação de multidão por computador é uma alternativa melhor. Os estádios de futebol são exemplos de ambientes que podem apresentar risco para as vidas das pessoas no caso de uma evacuação de emergência. O objetivo principal deste trabalho é ganhar compreensão sobre os aspectos inerentes ao problema de simulação de evacuação de emergência. Para isso, foi proposto um novo modelo para evacuação de multidão baseado no modelo de autômatos celulares. A fim de avaliar o modelo proposto, testes em diferentes situações foram realizados. Foi mostrado que o modelo proposto é capaz de simular a evacuação em ambientes complexos de uma forma eficiente.

Depuis plusieurs dizaines d’années, la modélisation du vivant est un enjeu majeur qui nécessite de plus en plus de travaux dans le domaine de la simulation. En effet, elle ouvre la porte à toute une palette d’applications : l’aide à la décision en environnement et en écologie, l’aide à l’enseignement, l’aide à la décision pour les médecins, l’aide à la recherche de nouveaux traitements pharmaceutiques et la biologie dite « prédictive », etc. Avant de pouvoir aborder un problème, il est nécessaire de pouvoir modéliser de façon précise le système biologique concerné en précisant bien les questions auxquelles devra répondre le modèle. La manipulation et l’étude de systèmes complexes, les systèmes biologiques en étant l’archétype, pose, de façon générale, des problèmes de modélisation et de simulation. C’est dans ce contexte que la société Integrative BioComputing (IBC) développe depuis le début des années 2000 un prototype d’une Plateforme Générique de Modélisation et de Simulation (la PGMS) dont le but est de fournir un environnement pour modéliser et simuler plus simplement les processus et les fonctions biologiques d’un organisme complet avec les organes le composant. La PGMS étant une plateforme générique encore en phase de développement, elle ne possédait pas les performances nécessaires pour permettre de réaliser la modélisation et la simulation d’éléments importants dans des temps suffisamment courts. Il a donc été décidé, afin d’améliorer drastiquement les performances de la PGMS, de paralléliser et d’optimiser l’implémentation de celle-ci ; le but étant de permettre la modélisation et la simulation d’organes complets dans des temps acceptables. Le travail réalisé au cours de cette thèse a donc consisté à traiter différents aspects de la modélisation et de la simulation de systèmes biologiques afin d’accélérer les traitements de ceux-ci. Le traitement le plus gourmand en termes de temps de calcul lors de l’exécution de la PGMS, le calcul des champs physicochimiques, a ainsi fait l’objet d’une étude de faisabilité de sa parallélisation. Parmi les différentes architectures disponibles pour paralléliser une telle application, notre choix s’est porté sur l’utilisation de GPU (Graphical Processing Unit) à des fins de calculs généralistes aussi couramment appelé GPGPU (General-Purpose computation on Graphics Processing Units). Ce choix a été réalisé du fait, entre autres, du coût réduit du matériel et de sa très grande puissance de calcul brute qui en fait une des architectures de parallélisation les plus accessibles du marché. Les résultats de l’étude de faisabilité étant particulièrement concluant, la parallélisation du calcul des champs a ensuite été intégrée à la PGMS. En parallèle, nous avons également mené des travaux d’optimisations pour améliorer les performances séquentielles de la PGMS. Le résultat de ces travaux est une augmentation de la vitesse d’exécution d’un facteur 18,12x sur les simulations les plus longues (passant de 16 minutes pour la simulation non optimisée utilisant un seul cœur CPU à 53 secondes pour la version optimisée utilisant toujours un seul cœur CPU mais aussi un GPU GTX500). L’autre aspect majeur traité dans ces travaux a été d’améliorer les performances algorithmiques pour la simulation d’automates cellulaires en trois dimensions. En effet, ces derniers permettent aussi bien de simuler des comportements biologiques que d’implémenter des mécanismes de modélisation tels que les interactions multi-échelles. Le travail de recherche s’est essentiellement effectué sur des propositions algorithmiques originales afin d’améliorer les simulations réalisées par IBC sur la PGMS. L’accélération logicielle, à travers l’implémentation de l’algorithme Hash‑Life en trois dimensions, et la parallélisation à l’aide de GPGPU ont été étudiées de façon concomitante et ont abouti à des gains très significatifs en temps de calcul. / For some years, living matter modeling has been a major challenge which needs more and more research in the simulation field. Indeed, the use of models of living matter have multiple applications: decision making aid in environment or ecology, teaching tools, decision making aid for physician, research aid for new pharmaceutical treatment and “predictive” biology, etc. But before being able to tackle all these issues, the development of a correct model, able to give answer about specific questions, is needed. Working with complex systems –biologic system being the archetype of them– raises various modeling and simulation issues. It is in this context that the Integrative BioComputing (IBC) company have been elaborating, since the early 2000s, the prototype of a generic platform for modeling and simulation (PGMS). Its goal is to provide a platform used to easily model and simulate biological process of a full organism, including its organs. Since the PGMS was still in its development stage at the start of my PhD, the application performance prevented the modeling and simulation of large biological components in an acceptable time. Therefore, it has been decide to optimize and parallelize its computation to increase significantly the PGMS performances. The goal was to enable the use of the PGMS to model and simulate full organs in acceptable times. During my PhD, I had to work on various aspects of the modeling and simulation of biological systems to increase their process speed. Since the most costly process during the PGMS execution was the computation of chemical fields, I had to study the opportunity of parallelizing this process. Among the various hardware architectures available to parallelize this application, we chose to use graphical processing units for general purpose computation (GPGPUs). This choice was motivated, beside other reasons, by the low cost of the hardware compared to its massive computation power, making it one of the most affordable parallel architecture on the market. Since the results of the initial feasibility study were conclusive, the parallelization of the fields computation has been integrated into the PGMS. In parallel to this work, I also worked on optimizing the sequential performance of the application. All these works lead to an increase of the software performances achieving a speed-up of 18.12x for the longest simulation (from 16 minutes for the non-optimized version with one CPU core to 53 seconds for the optimized version, still using only one core on the CPU but also a GPU GTX500). The other major aspect of my work was to increase the algorithmic performances for the simulation of three-dimensional cellular automata. In fact, these automata allow the simulation of biological behavior as they can be used to implement various mechanisms of a model such as multi-scale interactions. The research work consisted mainly in proposing original algorithms to improve the simulation provided by IBC on the PGMS. The sequential speed increase, thanks to the three-dimensional Hash Life implementation, and the parallelization on GPGPU has been studied together and achieved major computation time improvement.

abstract: What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed. / Dissertation/Thesis / Doctoral Dissertation Physics 2017

abstract: In material science, microstructure plays a key role in determining properties, which further determine utility of the material. However, effectively measuring microstructure evolution in real time remains an challenge. To date, a wide range of advanced experimental techniques have been developed and applied to characterize material microstructure and structural evolution on different length and time scales. Most of these methods can only resolve 2D structural features within a narrow range of length scale and for a single or a series of snapshots. The currently available 3D microstructure characterization techniques are usually destructive and require slicing and polishing the samples each time a picture is taken. Simulation methods, on the other hand, are cheap, sample-free and versatile without the special necessity of taking care of the physical limitations, such as extreme temperature or pressure, which are prominent issues for experimental methods. Yet the majority of simulation methods are limited to specific circumstances, for example, first principle computation can only handle several thousands of atoms, molecular dynamics can only efficiently simulate a few seconds of evolution of a system with several millions particles, and finite element method can only be used in continuous medium, etc. Such limitations make these individual methods far from satisfaction to simulate macroscopic processes that a material sample undergoes up to experimental level accuracy. Therefore, it is highly desirable to develop a framework that integrate different simulation schemes from various scales to model complicated microstructure evolution and corresponding properties. Guided by such an objective, we have made our efforts towards incorporating a collection of simulation methods, including finite element method (FEM), cellular automata (CA), kinetic Monte Carlo (kMC), stochastic reconstruction method, Discrete Element Method (DEM), etc, to generate an integrated computational material engineering platform (ICMEP), which could enable us to effectively model microstructure evolution and use the simulated microstructure to do subsequent performance analysis. In this thesis, we will introduce some cases of building coupled modeling schemes and present the preliminary results in solid-state sintering. For example, we use coupled DEM and kinetic Monte Carlo method to simulate solid state sintering, and use coupled FEM and cellular automata method to model microstrucutre evolution during selective laser sintering of titanium alloy. Current results indicate that joining models from different length and time scales is fruitful in terms of understanding and describing microstructure evolution of a macroscopic physical process from various perspectives. / Dissertation/Thesis / Doctoral Dissertation Materials Science and Engineering 2018

Made available in DSpace on 2015-03-26T13:35:15Z (GMT). No. of bitstreams: 1 texto completo.pdf: 2208057 bytes, checksum: 45a242fadca486c484bfa0df0f61ec59 (MD5) Previous issue date: 2011-07-22 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The characterization of fractals and the search for general rules and mechanisms for description of non-linear phenomena brought the attention of the scientific community to the interdisciplinary area of complex systems. Complex phenomena can be found in almost every branch of natural science. One example is the simulation using cellular automata of self-organization in life. This work focuses on cellular automata models to simulate the growth of branched structures in animal body guided by the characteristics of interactions in cell migration. Our models are guided by the dynamics of angiogenesis and neurogenesis, apparently two different mechanisms that can be classified under the same rules regarding local interactions and emergent behaviors. The proposed models can be very useful in studies of neurological diseases and cancer therapies. / A caracterização de estruturas fractais e a busca por mecanismos ou regras universais para descrição de diversos fenômenos não-linares fez com que a comunidade científica se voltasse para uma área que pode ser considerada uma das pioneiras na interdiciplinaridade: os Sistemas Complexos. Praticamente toda disciplina possui em seu domínio fenômenos complexos. Uma das linha de destaque dessa área são as simulações em autômatos celulares, principalmente quando voltada para estudos de auto-organização em seres vivos. O presente trabalho propõe uma modelagem em autômatos celulares para simulação de crescimento de estruturas ramificadas no organismo animal guiadas pelas interações características da migração celular. Nosso modelo foi baseado na angiogênese e na neurôgenese, estruturas que são aparentemente distintas, mas que na verdade pertencem a um mesmo grupo se classificados quanto às regras de interações locais e seus comportamentos emergentes. Esse modelo pode ser de grande utilidade no estudo de doenças relacionadas ao sistema nervoso e de terapias de combate ao câncer.

Made available in DSpace on 2015-05-14T12:14:21Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2227394 bytes, checksum: 05a68822cdf04f42c1f50d5c368cac63 (MD5) Previous issue date: 2011-02-28 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / wide range of pathogens are transmitted by a combination of horizontal and vertical transmission; among these are microsporodians, helminths, bacteria and viruses of plants and animals, including important human pathogens such as HIV, HTLV-1, cytomegalovirus, several hepatitis viruses and herpes simplex [Proc. R. Soc. Lond. B 260: 321-327]. In this work, the vertical parasite spreading from parent to offspring and horizontal transmission through infection in a population of moving individuals are discussed using a probabilistic cellular automata implemented on a square lattice. In our model, we generalize the automata proposed in [J. Phys. A : Math. Gen. 27: 1585-1597] to include the vertical transmission. The local rule consists of two subrules: the first one, applied synchronously, models infection, birth and death processes; the second, applied sequentially, describes the motion of individuals. In this model, endemic states may occur (susceptible and infected individuals coexisting) or a disease-free state (without infected). It is worth mentionins that a state in which the entire population becomes infective is possible in the case of perfect vertical transmission, i.e. infected parents give birth only to infected offspring. Moreover, the stability of these states may be analised using a mean-field approximation or grafically verified from the numerical simulations. / Uma ampla faixa de patógenos são propagados por uma combinação de transmissão horizontal e vertical, dentre os quais podemos destacar: microesporídeos, helmintos, bactérias, fungos e vírus de plantas e animais, incluindo importantes microorganismos parasitas de humanos como o HIV, HTLV-1, cytomegalovírus, vários tipos de hepatite e herpes simples [Proc. R. Soc. Lond. B 260: 321-327 (1995)]. Neste trabalho, a transmissão vertical (infecção do genitor para os filhos) e a transmissão horizontal (infecção por contágio) numa população de indivíduos em movimento são discutidos usando um autômato celular probabilístico implementado numa rede quadrada. Em tal modelo, generalizamos o autômato proposto em [J. Phys. A : Math. Gen. 27: 1585-1597 (1994)] para incluir a transmissão vertical. A regra local consiste de duas subregras: a primeira modela de maneira sincronizada os nascimentos, as mortes e as infecções; já a segunda, aplicada sequencialmente, descreve o movimento dos indivíduos. Neste modelo é possível um estado endêmico (suscetíveis coexistindo com infectados) ou um estado livre de doenças (sem infectados). Salienta-se que um estado em que toda a população torna-se infectada é possível no caso de transmissão vertical perfeita, i.e. pais infectados possuem apenas descendentes infectados. Inclusive, a estabilidade destes estados pode ser analizada na aproximação de campo médio para este modelo, ou verificada através dos gráficos dos resultados das simulações numéricas.

O estadunidense Edward Fredkin, um pioneiro na área de computação, é conhecido por defender a hipótese do mundo natural ser fundamentalmente um sistema de computação digital se partirmos do princípio de que todas as grandezas físicas são discretas, de modo que cada unidade mínima de espaço e tempo possa assumir apenas uma quantidade finita de estados possíveis. Nesse cenário, as transições de estado do universo nas escalas mais elementares poderiam ser representadas por modelos de autômatos celulares, sistemas computacionais formados de unidades espaciais básicas (células) que modificam seus estados em dependência de uma regra de transição que toma o próprio estado da célula com relação às unidades vizinhas. Quando as mudanças de estados das células são consideradas em escalas maiores, é possível notar um comportamento coletivo que parece seguir uma regra própria, não contemplada na programação básica atuando no nível das células. Fredkin acredita que o nível mais microscópico de nosso universo funcione como um autômato celular e, quando sua computação é tomada em maiores escalas, o padrão coletivo é identificado com os elementos que definimos em nossa física atual como elétrons, moléculas, pedras, pessoas e galáxias, ainda que todos esses elementos macroscópicos sejam apenas o resultado de uma computação alterando estados presentes em unidades mínimas de espaço. Diante disso, a intenção deste trabalho é mostrar que a conjectura de Fredkin pode ser interpretada como uma hipótese reducionista, uma vez que todo sistema explicado por nossas teorias físicas podem ser completamente definidos em termos de uma estrutura computacional. / Edward Fredkin, an American computer pioneer, is known for defending that the natural world be fundamentally a digital computing system, assuming that all physical quantities are discrete, in a way that each unit of space and time can only attain a finite number of possible states. In this scenario, the state transitions of the universe, taking place in the most elementary scales, could be represented by cellular automata models, computer systems formed by basic space units (cells) that modify their states in dependence on a transition rule that takes the state of the cell itself with respect to neighboring units. When cell state changes are considered on larger scales, it is possible to notice a collective behavior that seems to follow a rule of its own, not contemplated in basic programming at the cell level. Fredkin believes that the most microscopic level of our universe works as a cellular automaton and when its computation is taken at larger scales, the collective pattern is identified with the elements we define in our current physics as electrons, molecules, stones, people and galaxies, although all these macroscopic elements are only the result of a computation altering the states in minimum space units. The purpose of this work is to show that Fredkin\'s conjecture can be interpreted as a reductionist hypothesis, since every system explained by our physical theories can be completely defined in terms of a computational structure.

Duas questões fundamentais no estudo da evolução pré-biótica (origem da vida) referem-se à estabilidade dos primeiros organismos ou replicadores e à possibilidade do surgimento de organismos complexos através de mutações de organismos mais simples. Esses problemas têm sido tratados quase que exclusivamente no contexto determinístico da cinética química de meios perfeitamente homogêneos, que é equivalente à formulação de campo médio da física estatística. Nesta tese, abordamos essas questões utilizando modelos de replicadores na rede que evoluem no tempo de forma síncrona (autômato celular), dando ênfase ao caso limite em que os replicadores são mantidos fixos nos sítios da rede (processo de contato). Encontramos dois regimes estacionários bem definidos: o regime absorvente ou vácuo e o regime ativo caracterizados, respectivamente, pela ausência e presença de replicadores na rede. Esses regimes são separados por transições de fase cuja natureza depende do mecanismo de reprodução dos replicadores. Essas transições são investigadas de maneira sistemática utilizando-se a técnica de espalhamento de Grassberger e de La Torre em que a evolução temporal de uma pequena colônia de replicadores colocada no centro de uma rede infinita vazia \\\'e acompanhada. Em particular, através do cálculo de expoentes críticos dinâmicos mostramos que, as transições contínuas observadas, pertencem à classe de universalidade da percolação direcionada. Complementamos esse estudo investigando a probabilidade de que uma pequena colônia de replicadores invada uma população de replicadores residentes de outra espécie. Ao contrário dos resultados de campo médio, mostramos que no caso de processos de contato, replicadores mais complexos (por exemplo, assexuados) podem invadir uma população estabelecida de replicadores mais simples (por exemplo, assexuados). Em concordância com os resultados de campo médio, encontramos que nunca ocorre coexistência entre replicadores distintos no equilíbrio. Finalmente, utilizando a técnica de espalhamento mencionada, investigamos de forma sistemática um modelo para formação de úlceras devido à infecção do vírus da herpes (HSV-I) no tecido epitelial da córnea. O modelo considerado tenta explicar as diferentes formas de úlceras-dendríticas e amebóides-resultantes desta infecção como um resultado natural do espalhamento do vírus num tecido epitelial formado por células com diferentes graus de susceptibilidade à infecção. Em particular, mostramos que a transição de fase separando os regimes caracterizados pelas diferentes morfologias pertence à classe de universalidade da percolação ordinária. / Two fundamental questions in the study of prebiotic evolution (origin of life) are concerned to the requisites for the persistence of small colonies of self-replicating molecules (replicators) and to the possibility that complex organisms evolve from simpler organisms as a result of mutations. These issues have been studied mainly in the chemical kinetics formulation of well-mixed medium, which is similar to the mean-field limit of statistical physics. In this work, we address these issues using a cellular automaton formulation, in which the replicators are kept fix in the lattice sites (contact process). In the stationary regime, we find that the system can be characterized by the presence (active phase) and the absence (empty phase) of replicators in the lattice. The detailed study of the phase transitions separating those two phases is carried out using the spreading analysis of Grassberger and de La Torre, in which one concentrates on the spreading behavior of a few active cells in the center of an otherwise empty infinite lattice. The nature of the phase transition, whether continuous or discontinuous, depends on the mechanisms of replication. In particular, in the case that the phase transition is continuous, we find that it is in the universality class of the directed percolation. Complementing this study, we irivestigate the possibility that a small colony of replicators invade a settled population of replicators of another species. Contrary to the results of the mean-field limit, we show that in the contact process limit, complex replicators (such as sexual reproducing ones) have a nonvanishing probability to invade a settled population of simpler replicators (such as asexual reproducing ones). In agreement with the mean-field results, we find that two different species of replicators can never coexist in an equilibrium situation. Finally, using the spreading analysis mentioned before we study the critical properties of a cellular automaton model proposed to describe the spreading of infection of the Herpes Simplex Virus (HSV-I) in the corneal tissue. The model takes into account different cell susceptibilities to the viral infection, as suggested by experimental findings, in order to explain the different shapes of the ulcers - dentritic and amoeboid - that result from the infection. We show that the phase transition separating the regimes where one of the shapes dominates is in the universality class of the ordinary percolation.