
Sanz, Cecilia Verónica
This book is an applied introduction to the problems and solutions of modern computer vision. It offers a collection of selected, welltested methods (theory and algorithms), aiming to balance difficulty and applicability. It can be considered a starting point to understand and investigate the literature of computer vision, including conferences, journals, and Internet sites.

Simari, Guillermo Ricardo
Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

Tinetti, Fernando Gustavo
This book makes a clear presentation of the traditional topics included in a course of undergraduate parallel programming. As explained by the authors, it was developed from their own experience in classrooms, introducing their students to parallel programming. It can be used almost directly to teach basic parallel programming.

Tinetti, Fernando Gustavo
This book makes a clear presentation of the traditional topics included in a course of undergraduate parallel programming. As explained by the authors, it was developed from their own experience in classrooms, introducing their students to parallel programming. It can be used almost directly to teach basic parallel programming.

Wierzchon, Slawomir T.
The paper provides a brief introduction into a relatively new discipline: artificial immune systems (AIS). These are computer systems exploiting the natural immune system (or NIS for brevity) metaphor: protect an organism against invaders. Hence, a natural field of applications of AIS is computer security. But the notion of invader can be extended further: for instance a fault occurring in a system disturbs patterns of its regular functioning. Thus fault, or anomaly detection is another field of applications. It is convenient to represent the information about normal and abnormal functioning of a system in binary form (e.g. computer programs/viruses are...

Wierzchon, Slawomir T.
The paper provides a brief introduction into a relatively new discipline: artificial immune systems (AIS). These are computer systems exploiting the natural immune system (or NIS for brevity) metaphor: protect an organism against invaders. Hence, a natural field of applications of AIS is computer security. But the notion of invader can be extended further: for instance a fault occurring in a system disturbs patterns of its regular functioning. Thus fault, or anomaly detection is another field of applications. It is convenient to represent the information about normal and abnormal functioning of a system in binary form (e.g. computer programs/viruses are...

Fernandez, Natalia; Alfonso, Hugo; Gallard, Raúl Hector
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can be extended to multiobjective optimization, simulation of complex systems and multimodal function optimization. In this later case a conventional evolutionary algorithm tends to group the final population around the fittest individual. Thus, other areas of interest in the search process are lost. Niching methods permits the maintenance of solutions located around these areas of interest. This contribution briefly describe problems preventing niche formation in conventional genetic algorithms, a crowding...

Fernandez, Natalia; Alfonso, Hugo; Gallard, Raúl Hector
Niche formation allows evolutionary algorithms to be used when the location and maintenance of multiple solutions appertaining to diverse areas of the phenotypic space is required. Consequently the application field can be extended to multiobjective optimization, simulation of complex systems and multimodal function optimization. In this later case a conventional evolutionary algorithm tends to group the final population around the fittest individual. Thus, other areas of interest in the search process are lost. Niching methods permits the maintenance of solutions located around these areas of interest. This contribution briefly describe problems preventing niche formation in conventional genetic algorithms, a crowding...

Abásolo Guerrero, María José; De Giusti, Armando Eduardo; Blat Gimeno, Josep
Interactive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that...

Abásolo Guerrero, María José; De Giusti, Armando Eduardo; Blat Gimeno, Josep
Interactive visualisation of triangulated terrain surfaces is still a problem for virtual reality systems. A polygonal model of very large terrain data requires a large number of triangles. The main problems are the representation rendering efficiency and the transmission over networks. The major challenge is to simplify a model while preserving its appearance. A multiresolution model represents different levels of detail of an object. We can choose the preferable level of detail according to the position of the observer to improve rendering and we can make a progressive transmission of the different levels. We propose a multiresolution triangulation scheme that...

Esquivel, Susana Cecilia; Gatica, Claudia R.; Gallard, Raúl Hector
Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which improve a single solution. All these algorithms share common features: reproduction, random variation, competition and selection of individuals. During our research it was evident that some components of EAs should be reexamined. Hence, specific topics such as multiple crossovers per couple and its enhancements, multiplicity of parents and crossovers and their application to single and multiple criteria optimization problems, adaptability, and parallel genetic algorithms, were proposed...

Esquivel, Susana Cecilia; Gatica, Claudia R.; Gallard, Raúl Hector
Evolutionary computation (EC) has been recently recognized as a research field, which studies a new type of algorithms: Evolutionary Algorithms (EAs). These algorithms process populations of solutions as opposed to most traditional approaches which improve a single solution. All these algorithms share common features: reproduction, random variation, competition and selection of individuals. During our research it was evident that some components of EAs should be reexamined. Hence, specific topics such as multiple crossovers per couple and its enhancements, multiplicity of parents and crossovers and their application to single and multiple criteria optimization problems, adaptability, and parallel genetic algorithms, were proposed...

Gonzalez, Jesús Alberto; León, Coromoto; Piccoli, María Fabiana; Printista, Alicia Marcela; Roda García, José Luis; Rodríguez, Casiano; Sande, Francisco de
The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the wellknown Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and...

Gonzalez, Jesús Alberto; León, Coromoto; Piccoli, María Fabiana; Printista, Alicia Marcela; Roda García, José Luis; Rodríguez, Casiano; Sande, Francisco de
The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the wellknown Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and...

Pons, Claudia; Baum, Gabriel Alfredo; Kutsche, RalfDetlef
In this paper we define an evolution mechanism with formal semantics using the metamodeling methodology [Geisler et al.98] based on dynamic logic. A remarkable feature of the metamodeling methodology is the ability to define the relation of intentional and extensional entities within one level, allowing not only for the description of structural relations among the modeling entities, but also for a formal definition of structural
constraints and dynamic semantics of the modeled entities. While dynamic semantics on the extensional level means runtime behavior, dynamic semantics on intentional level describes model evolution in the system life cycle.

Pons, Claudia; Baum, Gabriel Alfredo; Kutsche, RalfDetlef
In this paper we define an evolution mechanism with formal semantics using the metamodeling methodology [Geisler et al.98] based on dynamic logic. A remarkable feature of the metamodeling methodology is the ability to define the relation of intentional and extensional entities within one level, allowing not only for the description of structural relations among the modeling entities, but also for a formal definition of structural
constraints and dynamic semantics of the modeled entities. While dynamic semantics on the extensional level means runtime behavior, dynamic semantics on intentional level describes model evolution in the system life cycle.