People
prof. Ing. Zdeněk Votruba, CSc.

2023, Neural Network World, 33 (5), p. 397-412), ISSN 1210-0552

Today's quick development of artificial intelligence (AI) brings us to the questions that have until recently been the domain of philosophy or even sciencefiction. When can be a system considered an intelligent one? What is a consciousness and where it comes from? Can systems gain consciousness? It is necessary to have in mind, that although the development seems to be a revolutionary one, the progress is successive, today’s technologies did not emerge from thin air, they are firmly built on previous findings. As now some wild thoughts and theories where the AI development leads to have arisen, it is time to look back at the background theories and summarize, what do we know on the topics of intelligence, consciousness, where they come from and what are different viewpoints on these topics. This paper combines the findings from different areas and present overview of different attitudes on systems consciousness and emphasizes the role of systems sciences in helping the knowledge in this area.

2023, ISBN 978-80-11-03295-1

We present a brief description of some mechanism of brain activity and a list of the analyzes used and the considerations resulting from them. In order to better navigate the complex structure and function of the brain for both practical and scientific reasons, we use a variety of methods. On the other hand, it is anamnesis, clinical examination and follow-up, and structural and functional diagnostics. Finally, it is the creation of parabolic equations, i.e. simulation, modeling, e.g. we compare some properties of the brain with mathematical logic models (MLM) and vice versa. The brain and MLM teach each other. The simulation process is independent of the material and structural nature of the model. Models are usually electronic and digital.

2022, ISBN 978-80-01-07105-2, ISSN 2336-5382

2022, ISBN 9788011009939

Cil práce je zlepšovat psychologickou diagnostiku pomoci porovnání kvalitativně a kvantitativně analyzovaného EEG záznamu s aktivovaným chovaným. Jde o směr zkoumaní vývoje vědomi čili noogenese. Používáme řadu analýz EEG křivky a současně zkrácených psychotestů a obě metody vzájemně korelujeme. Pokud možno přidružujeme další metody jako je PET, fMR, plysomnografii nebo NIRS. Domníváme se, že lze v EEG křivce nalézt definovatelné změny, které souvisí s vyššími psychologickými funkcemi. V životě dítěte jsou občas okamžiky přinášející pochyby o jeho správném vývoji, a proto by bylo dobré vyjádřit se odborně o jeho stavu u lékaře i v pedagogicko-psychologické poradně.

2020, 2020 Smart City Symposium Prague (SCSP), Vienna, IEEE Industrial Electronic Society), ISBN 978-1-7281-6821-0

This paper is an introductory part of studies focused on various aspects of the ageing of data /information/ knowledge.

2020, Neural Network World Journal, 2020 (1), p. 45-53), ISSN 1210-0552

This paper introduces a possibility of application of parametric sensitivity appearing in processes of decision making in systems represented by the general production functions of the Tinbergen type, depending on information content, information flow and qualification of human resources. The so-called parametric sensitivity considering the information content I as an ordering parameter, dependent on the information flow, applied on production function. The theory of production function describes the relation between physical outputs of a production process and physical inputs, i.e. factors of production. Finally, the influence of knowledge in information content I, leading to correct decision, is demonstrated through the parametric sensitivity concept. For this invention, J. Tinbergen and R. Frisch achieved in 1969 the "Nobel price of the Swedish National Bank". Besides, the production functions theory surprisingly represents also a tool for finding the reasons of living bodies behavior.

2019, Industrial Applications of Holonic and Multi-Agent Systems, Wien, Springer), p. 41-51), ISBN 978-3-030-27877-9, ISSN 0302-9743

Basic concepts and ideas of uncertain systems alliances are briefly overviewed. Then the strength of the alliance joints is analyzed via medium mutual information measure. This approach can help to estimate the value/ importance of respective bonds within the alliance, which is important in alliances with significant uncertainty.

2019, Neural Network World, 29 (6), p. 373-379), ISSN 1210-0552

Artificial systems play an extremely important role in human life. Each day, almost all people on the Earth have to interact with various complex systems, which are of a very different nature and target application. These all system structures and their whole sets can be of various degrees of complexity and can be discriminated into many categories. These three can be considered as their main kinds: • artificial systems, • living systems, • natural systems. All of them could have very various behaviours but some aspects – as well as their theoretical backgrounds – are universal. Artificial systems are those created by the human, so mostly by human will and decisions.

2018, ISBN 978-80-7270-058-5

Publikace Města budoucnosti pojednává o účelném využití moderních technologií pro lepší správu a management měst s ohledem na jejich udržitelný rozvoj a kvalitu života obyvatel města.

2018, Neural Network World, 28 (3), p. 225-239), ISSN 1210-0552

The paper presents an information model for representation of brain linear and nonlinear resonance phenomena based on information nullors. In the brain functions the rhythms and quasi periodicity of processes in neural networks play the outstanding (significant) role. It is why adaptive resonance theory (ART) including resonant effects has been studied for a long time by many authors. The periodicity in the transfers of signals between the long-term memory (LTM) and short-term memory (STM) creates a possibility of resonance system structure. LTM with information content representing expectations and STM covering sensory information in resonance process offer effective learning. Nonlinear adaptive resonance creates conditions for new knowledge, or inventory observation. In the paper this feature is newly modelled by an information gyrator that best fits these linear and non-linear phenomena.

2018

2018, ISBN 978-88-255-0801-7

The significance and usefulness of Systems–Complexes depends on their reliability. Basic contours of respective theory were recognized in recent years. The body of knowledge of reliability is also an important background for globally important studies of systems sustainability, resilience and survival. Being interested in these areas already since 80 ties, the authors have investigated various aspects of these problems, related to artificial or biological systems. Now they feel that it is right time to summarize the important items of this theory in a book based on unified set of paradigms.