Roberto Serra – författare

Cellular Automata (CA), about to enter their fifties, are coming of age, seen by the breadth and quality of CA-related research carried out worldwide, as well as by the appearance of interesting applications to real world problems. The papers collected in this book, presented at ACRI 98 (Third Conference on Cellular Automata for Research and Industry -7-9 October 1998), further demonstrate the vitality of this line ofresearch. Until some years ago, a researcher interested in dynamical modelling of spatially of the partial extended systems had only one language at his disposal, namely that differential equations (PDE). These are wonderful tools to use when an analytical solution can be found or a perturbative approach can provide a good approximation of the observed phenomena. The use of digital computers has enormously expanded the explanatory and predictive power of partial differential equations by allowing one to treat cases which had been outside the scope of a "pen and pencil" approach. However, it has also opened up a way to new formalisms which are able to describe interesting phenomena and are, at the same time, well-suited for digital simulation.

This volume contains the papers presented at the 3rd Conference on Cellular Automata for Research and Industry, ACRI 8, held in Trieste, Italy, 7-9 October 1998. The conference aimed to present an international forum for researchers who are active in this field, as well as for those interested in evaluating the possibility of applying them in their own fields. Cellular automata are used in several fields, including the simulation of different kinds of dynamical systems (physical, biological, socio-economical), machine vision, parallel computation, and the theoretical analysis of complex dynamics.

This book constitutes the refereed post proceedings of the 17th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2023, held in Venice, Italy, during September 6–8, 2023. The 30 full papers included in this book were carefully reviewed and selected from 55 submissions.

After a brief description of the known facts and main hypotheses, mathematical and computational models of protocells are discussed: they should complement laboratory experiments, allowing rapid explorations of the dynamical properties of several alternative types of protocell architectures.

How life can emerge in a lifeless environment is one of the major open scientific challenges. This book pays particular attention to self-organization phenomena that might have led to the appearance of the first protocells, i.e. cell-like structures, much simpler than present-day cells, endowed with some primitive kinds of metabolism and heredity. After a brief description of the known facts and main hypotheses, mathematical and computational models of protocells are discussed: they should complement laboratory experiments, allowing rapid explorations of the dynamical properties of several alternative types of protocell architectures. Given the great uncertainties about the actual origin of life, it seems impossible to provide a detailed and complete reconstruction of the first life forms. It is therefore necessary to identify plausible pathways, highlighting the main physical and chemical processes “towards life” that can take place. Generic models, which are abstract enough to encompass different specific hypotheses, are particularly relevant, as they allow one to identify properties which are common to several different detailed scenarios. They are widely discussed, and a particular case is described in detail, namely that of synchronization between the rate of molecular replication and that of reproduction of the whole protocell, which is a necessary condition for sustainable growth of a population and a prerequisite for further evolution. Using generic models, it is shown that such synchronization spontaneously emerges in successive generations, under very general assumptions.  The book also contains extensive descriptions of the emergence of long polymers, of autocatalytic sets and of the interactions between protocells and their environments. The book is not meant only for specialists, but also for scientists working in different fields, as well as for laymen with an interest in science. It requires a basic knowledge of chemistry and biology, and an interest in simulation models.

This book constitutes the revised selected papers of the 12th Italian Workshop on Advances in Artificial Life, Evolutionary Computation, WIVACE 2017, held in Venice, Italy, in September 2017.The 23 full papers presented were thoroughly reviewed and selected from 33 submissions. They cover the following topics: physical-chemical phenomena; biological systems; economy and society; complexity; optimization.

This book constitutes the revised selected papers of the 12th Italian Workshop on Advances in Artificial Life, Evolutionary Computation, WIVACE 2017, held in Venice, Italy, in September 2017.The 23 full papers presented were thoroughly reviewed and selected from 33 submissions. They cover the following topics: physical-chemical phenomena; biological systems; economy and society; complexity; optimization.

This book constitutes the refereed proceedings of the 11th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2009, held in Reggio Emilia, Italy, in December 2009. The 50 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on knowledge representation and reasoning, machine learning, evolutionary computation, search, natural language processing, multi-agent systems and application.

This book constitutes the refereed proceedings of the 11th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2009, held in Reggio Emilia, Italy, in December 2009. The 50 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on knowledge representation and reasoning, machine learning, evolutionary computation, search, natural language processing, multi-agent systems and application.

This volume describes our intellectual path from the physics of complex sys­ tems to the science of artificial cognitive systems. It was exciting to discover that many of the concepts and methods which succeed in describing the self­ organizing phenomena of the physical world are relevant also for understand­ ing cognitive processes. Several nonlinear physicists have felt the fascination of such discovery in recent years. In this volume, we will limit our discussion to artificial cognitive systems, without attempting to model either the cognitive behaviour or the nervous structure of humans or animals. On the one hand, such artificial systems are important per se; on the other hand, it can be expected that their study will shed light on some general principles which are relevant also to biological cognitive systems. The main purpose of this volume is to show that nonlinear dynamical systems have several properties which make them particularly attractive for reaching some of the goals of artificial intelligence. The enthusiasm which was mentioned above must however be qualified by a critical consideration of the limitations of the dynamical systems approach. Understanding cognitive processes is a tremendous scientific challenge, and the achievements reached so far allow no single method to claim that it is the only valid one. In particular, the approach based upon nonlinear dynamical systems, which is our main topic, is still in an early stage of development.

This volume describes our intellectual path from the physics of complex sys­ tems to the science of artificial cognitive systems. It was exciting to discover that many of the concepts and methods which succeed in describing the self­ organizing phenomena of the physical world are relevant also for understand­ ing cognitive processes. Several nonlinear physicists have felt the fascination of such discovery in recent years. In this volume, we will limit our discussion to artificial cognitive systems, without attempting to model either the cognitive behaviour or the nervous structure of humans or animals. On the one hand, such artificial systems are important per se; on the other hand, it can be expected that their study will shed light on some general principles which are relevant also to biological cognitive systems. The main purpose of this volume is to show that nonlinear dynamical systems have several properties which make them particularly attractive for reaching some of the goals of artificial intelligence. The enthusiasm which was mentioned above must however be qualified by a critical consideration of the limitations of the dynamical systems approach. Understanding cognitive processes is a tremendous scientific challenge, and the achievements reached so far allow no single method to claim that it is the only valid one. In particular, the approach based upon nonlinear dynamical systems, which is our main topic, is still in an early stage of development.

The monograph discusses models of synthetic protocells, which are cell-like structures obtained from non-living matter endowed with some rudimentary kind of metabolism and genetics, but much simpler than biological cells. They should grow and proliferate, generating offsprings that resemble in some way the parent protocells with some variation, so that selection may take place. Sustainable protocell populations have not yet been obtained experimentally and mathematical models are therefore extremely important to address key questions concerning their synthesis and behavior. Different protocell “architectures” have been proposed and high-level abstract models like those that are presented in this book are particularly relevant to gain a better understanding of the different properites. These models are able to treat all the major dynamical phenomena in a unified framework, so they can be seen as “virtual laboratories” for protocell research. Particular attention is paid to the problem of synchronization of the fission rate of the whole protocell and the duplication rate of its "protogenetic" material, which is shown to be an emergent property that spontaneously develops in successive generations.The book is of interest for a broad range of scientists working in soft matter physics, chemistry and biology, interested in the role protocells may play on the development of new technologies with medical, environmental and industrial applications as well as scientists interested in the origin of life.

The monograph discusses models of synthetic protocells, which are cell-like structures obtained from non-living matter endowed with some rudimentary kind of metabolism and genetics, but much simpler than biological cells. They should grow and proliferate, generating offsprings that resemble in some way the parent protocells with some variation, so that selection may take place. Sustainable protocell populations have not yet been obtained experimentally and mathematical models are therefore extremely important to address key questions concerning their synthesis and behavior. Different protocell “architectures” have been proposed and high-level abstract models like those that are presented in this book are particularly relevant to gain a better understanding of the different properites. These models are able to treat all the major dynamical phenomena in a unified framework, so they can be seen as “virtual laboratories” for protocell research. Particular attention is paid to the problem of synchronization of the fission rate of the whole protocell and the duplication rate of its "protogenetic" material, which is shown to be an emergent property that spontaneously develops in successive generations.The book is of interest for a broad range of scientists working in soft matter physics, chemistry and biology, interested in the role protocells may play on the development of new technologies with medical, environmental and industrial applications as well as scientists interested in the origin of life.

The monograph discusses models of synthetic protocells, which are cell-like structures obtained from non-living matter endowed with some rudimentary kind of metabolism and genetics, but much simpler than biological cells. They should grow and proliferate, generating offsprings that resemble in some way the parent protocells with some variation, so that selection may take place. Sustainable protocell populations have not yet been obtained experimentally and mathematical models are therefore extremely important to address key questions concerning their synthesis and behavior. Different protocell “architectures” have been proposed and high-level abstract models like those that are presented in this book are particularly relevant to gain a better understanding of the different properites. These models are able to treat all the major dynamical phenomena in a unified framework, so they can be seen as “virtual laboratories” for protocell research. Particular attention is paid to the problem of synchronization of the fission rate of the whole protocell and the duplication rate of its "protogenetic" material, which is shown to be an emergent property that spontaneously develops in successive generations.The book is of interest for a broad range of scientists working in soft matter physics, chemistry and biology, interested in the role protocells may play on the development of new technologies with medical, environmental and industrial applications as well as scientists interested in the origin of life.