CoCalc as a Learning Tool for Neural Network Simulation in the Special Course "Foundations of Mathematic Informatics"

The role of neural network modeling in the learning content of the special course "Foundations of Mathematical Informatics" was discussed. The course was developed for the students of technical universities - future IT-specialists and directed to breaking the gap between theoretic computer science and it's applied applications: software, system and computing engineering. CoCalc was justified as a learning tool of mathematical informatics in general and neural network modeling in particular. The elements of technique of using CoCalc at studying topic "Neural network and pattern recognition" of the special course "Foundations of Mathematic Informatics" are shown. The program code was presented in a CoffeeScript language, which implements the basic components of artificial neural network: neurons, synaptic connections, functions of activations (tangential, sigmoid, stepped) and their derivatives, methods of calculating the network's weights, etc. The features of the Kolmogorov-Arnold representation theorem application were discussed for determination the architecture of multilayer neural networks. The implementation of the disjunctive logical element and approximation of an arbitrary function using a three-layer neural network were given as an examples. According to the simulation results, a conclusion was made as for the limits of the use of constructed networks, in which they retain their adequacy. The framework topics of individual research of the artificial neural networks is proposed.Comment: 16 pages, 3 figures, Proceedings of the 13th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer (ICTERI, 2018

Outline of a multilevel approach of the network society

Social and media networks, the Internet in particular, increasingly link interpersonal, organizational and mass communication. It is argued that this gives a cause for an interdisciplinary and multilevel approach of the network society. This will have to link traditional micro- and meso-level research of social and communication ties (Rogers, Granovetter a.o.) to the macro-level research of the network society at large (Castells a.o.).\ud Systems theory linked to a theory of communicative action establishes a potential basis for a multilevel theory. The systems theory described uses elements of a biologically inspired analysis of networks as complex adaptive systems and the mathematically inspired theory of random and scale-free networks recently elaborated by Barabási, Strogatz and Watts. The outline of the multilevel theory is summarized in ten statements about changing relationships in the network society: an information society with structures and modes of organization primarily shaped by social and media networks. \ud In the last section an inventory is made of the theoretical and methodological changes communication science will have to make to develop a general theory of the information and the network society in the perspective of communication

Playing Smart - Artificial Intelligence in Computer Games

Abstract: With this document we will present an overview of artificial intelligence in general and artificial intelligence in the context of its use in modern computer games in particular. To this end we will firstly provide an introduction to the terminology of artificial intelligence, followed by a brief history of this field of computer science and finally we will discuss the impact which this science has had on the development of computer games. This will be further illustrated by a number of case studies, looking at how artificially intelligent behaviour has been achieved in selected games

QUERIES SERVICE TIME RESEARCH AND ESTIMATION DURING INFORMATION EXCHANGE IN MULTIPROCESSOR SYSTEMS WITH “UNI BUS” INTERFACE AND SHARED MEMORY

Abstract. The issues connected with estimating service time of queries (transactions) during the information exchange in multiprocessor systems with a unibus interface and shared memory are analyzed and studied in the article. The article aims at developing and making research of models based on systems and queueing networks, the "processor-memory" subsystem, as well as estimating the queries service time during the information exchange in multiprocessor systems with shared memory. The subject matter of the study is the analysis of time delays associated with conflict situations occured during the realization of interprocessor exchange when many processors turn to the exchange unibusand memory. The object of the article research is the "processor-memory" subsystem of existing multiprocessor systems and well-known versions of the architecture of this subsystem . The main task defined by the authors of the scientific article is to develop and make research of mathematical models of the "processor-memory" subsystem of the mentioned systems and to estimate the processing time of inputting queries during the information exchange in systems with shared memory. Mathematical models for carrying out queries service time research have been proposed. Equations fordetermining the main probabilistic-temporal characteristics of the "processor-memory" subsystem have been presented. The mentioned probabilistic-temporal models have been developed using the theory of queueing networks and probability theory. In conclusion the authors make the main judgements about the work done. The mathematical models studied in the article make it possible to estimate the main probabilistic-temporal characteristics of multiprocessor systems without developing real models or prototypes. As a result some effect is achieved, because it is possible to estimate thecharacteristics of new multiprocessor computer systems and choose the most optimal ones without creating a real expensive systemKeywords: simulation, analytical model, imitation model, queueing network system, transaction, read-operation, record-operation, multiprocessor system, “processor-memory” subsystem, memory architecture, memory bandwidth, memory controller, memory latency, buffer element

The genetic code for cities – is it simpler than we thought?

September 200

Artificial Intelligence in the Context of Human Consciousness

Artificial intelligence (AI) can be defined as the ability of a machine to learn and make decisions based on acquired information. AI’s development has incited rampant public speculation regarding the singularity theory: a futuristic phase in which intelligent machines are capable of creating increasingly intelligent systems. Its implications, combined with the close relationship between humanity and their machines, make achieving understanding both natural and artificial intelligence imperative. Researchers are continuing to discover natural processes responsible for essential human skills like decision-making, understanding language, and performing multiple processes simultaneously. Artificial intelligence attempts to simulate these functions through techniques like artificial neural networks, Markov Decision Processes, Human Language Technology, and Multi-Agent Systems, which rely upon a combination of mathematical models and hardware