We introduce so-called biomata which represent a novel approach to the construction of self-reproducing automata within the automata theory. The design of our automata has been motivated by the ideas of cellular biology on the origin of life. Unlike the von Neumann's model our model replicates by fission and need not give much attention to the exact guiding of its own assemblage; rather, this process relies on self-assembly abilities of the respective parts produced by the biomaton from input objects not possessing such quality. The model represents an interesting fusion of computational and self-organizational processes.We believe that by capturing the basic aspects of the assumed origin of real life our modelling leads to a conceptually simpler and hence more plausible scenario of natural self-reproduction than the previous attempts did.

We introduce a computational model of a so-called globular universe which represents generalization of both classical cellular automata and contemporary models of self-assembly. Similarly as the latter mentioned model our model utilizes a multiset of globules which are endowed by self-organizing ability controlled by a finite state mechanism; these computational units are not fixed in a predetermined structure. The environment abounds in these units which are available at places where needed for a self-assembly of various objects. Within a globular universe we define the notion of self-reproducing evolutionary automaton. This notion refers to an automaton being at the beginning of a lineage of self-reproducing automata which leads to self-reproducing automata with arbitrary complex finite state control mechanisms via a series of mutations of intermediate automata. The ideas presented in this paper complement von Neumann's results on self-reproducing automata in a static universe by offering a precise definition of what is meant by "evolutionary self-reproduction" and by designing a dynamic nondeterministic universe with a self-reproducing self-assembling evolutionary automaton.

Multi-agent systems typically utilize a non-blocking asynchronous communication in order to achieve required flexibility and adaptability. High performance computing techniques exploit the current hardware ability of overlapping asynchronous communication with computation to load the available computer resources efficiently. On the contrary, widely used parallel processes modeling methodologies do not often allow for an asynchronous communication description. At the same time those models do not allow their user to select the granularity level and provide only a fixed set of machine and algorithm description quantities. In this work we addressed this issue and designed a new parallel processes modeling methodology. Its main features include an open set of atomic operations that are calculated and predicted for the algorithm in question, and the computer aided semi-automatic measuring of operation counts and approximation of cost functions. This allows not only for tuning the model granularity as well as accuracy according to user needs, but also to reach a such description complexity that would be very difficult to obtain without any computer aid.

Multi-agent systems typically utilize a non-blocking asynchronous communication in order to achieve required flexibility and adaptability. High performance computing techniques exploit the current hardware ability of overlapping asynchronous communication with computation to load the available computer resources efficiently. On the contrary, widely used parallel processes modeling methodologies do not often allow for an asynchronous communication description. At the same time those models do not allow their user to select the granularity level and provide only a fixed set of machine and algorithm description quantities. In this work we addressed this issue and designed a new parallel processes modeling methodology. Its main features include an open set of atomic operations that are calculated and predicted for the algorithm in question, and the computer aided semi-automatic measuring of operation counts and approximation of cost functions. This allows not only for tuning the model granularity as well as accuracy according to user needs, but also to reach a such description complexity that would be very difficult to obtain without any computer aid. We demonstrated that our approach gives good results on the parallel implementation of a selected generalized genetic algorithm. A model was constructed and its predictions compared with the reality on various computer architectures, including one parallel cluster machine. We also designed and implemented an open multi-agent system suitable for the above mentioned experiments and many others. This system synthesizes the areas of high performance computing, multi-agent systems and computational intelligence into an efficient and flexible means of running experiments.

World Wide Web obsahuje data, která jsou pro počítačové programy nesrozumitelná. Následkem toho je na něm obtížné některé věci zautomatizovat. Nedostatky současného webu by měl odstranit sémantický web, ve kterém data budou mít přesně popsaný význam. Zlepšení může přinést také v oblasti integrace, která je v případě dat pocházejících z webu velmi obtížná. Tento článek se zabývá integrací webových dat. Zaměřuje se na relační data ve formátu XML a navrhuje postupy základních integračních operací.

This paper describes an option to express our preferences in the framework of relational databases. Preferences have usually a form of a partial ordering. Therefore the question is how to deliver the semantics of ordering to a database system. The answer is quite straightforward.

Příspěvek popisuje provedenou studii proveditelnosti databázově orientované části systému zajišťujícím automatickou extrakci dat z webových zdrojů (formáty XHTML, XML, CSV). Úkolem této části je transformace dat do automaticky vygenerovaného relačního modelu, který může být následně užit pro realizaci myšlenek sémantického webu. V úvodní části je uvedena motivace pro implementaci takového nástroje. Součástí příspěvku je i částečné ohlédnutí za již implementovanými metodami, které autor v současné době zpracovává. V poslední části je nastíněna fuzzyfikace problematiky.

Advances in cellular mobile technology have engendered a new paradigm of computing, called mobile computing. New challenges have arisen and solutions are proposed based on various approaches. One of the most important challenges is security and now a day has been found ubiquitous in computing as whole. The paper is intended as a quick survey emphasizing security paradigm and also ad hoc networks are kept in mind and briefly discussed.

A formalism for the logical description of computational agents and multi-agent systems is given. It is explained how it such a formal description can be used to configure and reason about multi-agent systems realizing computational intelligence models. A usage within a real software system Bang 3 is demonstrated. The logical description of multiagent systems opens Bang 3 for interaction with ontology based distributed knowledge systems like the Semantic Web or the Knowledge Grid.

A multi-agent system targeted toward the area of computational intelligence modeling is presented. The purpose of the system is to allow both experiments and high-performance distributed computations employing hybrid computational models. The focus of the system is the interchangeability of computational components, their autonomous behavior, and emergence of new models.

We discuss two approaches to supervised learning, namely regularization networks and RBF networks, and demonstrate their performance on experiments. We claim that the performance of these two models is comparable, so the RBF networks can be used as a cheaper alternative to regularization networks.