IDAACS | Special Stream on Advanced Automatic Control and Information Technology

Special Stream on Advanced Automatic Control and Information Technology

This Stream is organized by scientists from Cracow University of Technology and Lviv Polytechnic National University

Today the information processes of management and control systems should be focused on information technology-oriented users, and the transition from procedural to descriptive models and evidence-based decision-making. It will allow users to interact effectively with information systems at all stages of their life cycle, getting support and explanations in solving their problems. The intelligent information system helps the person formulate and solve problems by integrating the problem solving tools with a known and unknown solution schemes, which may be built from an existing set of schemes or requires the creation of an entirely new scheme.

The development of information technology, artificial intelligence and automatics has created the conditions for the transition to adaptive technologies, in which the properties of mobility and flexibility are complemented by the ability to self-organize and self-development, which are provided by the mechanisms of generalization, classification, intellectual data mining and adaptation. To achieve this, adaptive systems need to demonstrate self-determination based on multi-level, structured and complex representations.

Effective implementation of the new concept is possible only in a comprehensive adaptive technology for the creation, implementation, operation and development of information systems, the application component which ensures full system functionality, and the interaction of components is ensured by the following system tools:

supporting the functioning of the application elements of the IT system based on the general model of the control and management objects and business processes and defining the methods of their implementation;
design based on a multi-level approach, which allows the system to be "expanded" through an iterative-sequential implementation process of system description mappings, starting from the conceptual, user-oriented level, and ending with the implementation language level, oriented towards a qualified programmer;
learning that gives technology the ability to self-development through finding and using patterns, adaptive behavior;
data and knowledge management, which gives the user the ability to work with data about the control and management object, models at all stages of the IT system life cycle, and allows the redefinition of object classes in the functioning process(es).

In terms of implementing this approach, we will be happy to discuss in our stream new models, methods, technologies and tools for use in the above mentioned areas.

Automatic Control

Internet of things: models, methods, technologies of design and implementation, successful products, experience.

Intelligent control: fuzzy control, methods of learning to deal with fuzzy and artificial neural networks.

Control systems in conditions of uncertainty: models and methods of control in conditions of uncertainty of external influences, the dynamics and the parameters of the system. We will be glad to see the application of both classical methods, such as statistical, and artificial intelligence methods.

Information Technologies

Description, design, implementation and development of information systems: models, methods, technologies, languages, tools, implementation experience.

Computer-aided information systems design technologies: modern agile-technologies of information systems design and experience of their implementation; languages and technologies of automated design of information systems architecture; technologies of information systems implementation on the basis of architecture.

Traditional areas of artificial intelligence. We are waiting for models and methods for the development of traditional areas of artificial intelligence: reasoning; presentation of problems and searching for solutions; theorem proving; representation and processing of knowledge; machine learning; communication; inaccuracy and uncertainty; image recognition; intellectual data mining; planning of navigation for mobile robots; planning; pattern processing and computer vision; digital conversion and signal processing in transport systems; intelligent computations (fuzzy logic, artificial neural networks, genetic algorithms and evolutionary modeling, and others).

Modern areas of artificial intelligence. We are waiting for models and methods for the development of the most modern areas of artificial intelligence: Deep Feedforward Networks (regularization, optimization, practical methodology, applications), Deep Learning Research (models, methods, , practical methodology, applications) and others.

Models and methods of knowledge presentation and processing, computer linguistics, constructive logic, image processing and other to ensure: involvement of management in the creation of information systems at all stages of their life cycle; providing the user with the ability to handle ready-made tasks and organizational impact on the business logic of management activities; teaching computers to language and problem solving; resolving the contradiction between the demands of simplicity of means of communication and the efficiency of systems.

Co-Chairs of the Stream