Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

Ontological Approach to Domain Knowledge Representation for Information Retrieval in Multiagent Systems

An ontological representation of buyer interests’ knowledge in process of e-commerce is proposed to use. It makes it more efficient to make a search of the most appropriate sellers via multiagent systems. An algorithm of a comparison of buyer ontology with one of e-shops (the taxonomies) and an e-commerce multiagent system are realised using ontology of information retrieval in distributed environment.

Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.

Formal Definition of Artificial Intelligence

* This publication is partially supported by the KT-DigiCult-Bg project.

About the Journal of RAAI ”News of Artificial Intelligence”

Beginning from 1991, Russian (initially Soviet) Association for Artificial Intelligence (RAAI) publishes the own journal ‘News of Artificial Intelligence’. The journal is founded on the initiative of the famous specialist in the field of Artificial Intelligence (AI), the first president of Soviet Association for Artificial Intelligence, the academician of Russian Academy of Natural Science (RANS), doctor of technical sciences (d.t.s.), professor D.A. Pospelov, which from 1991 up to 2001 was its main editor.

Application of the Artificial Intelligence Algorithms with a Cognitive Graphic as a Tool for a System Analysis of Electrophysiological Processes

Summarizing the accumulated experience for a long time in the polyparametric cognitive modeling of different physiological processes (electrocardiogram, electroencephalogram, electroreovasogram and others) and the development on this basis some diagnostics methods give ground for formulating a new methodology of the system analysis in biology. The gist of the methodology consists of parametrization of fractals of electrophysiological processes, matrix description of functional state of an object with a unified set of parameters, construction of the polyparametric cognitive geometric model with artificial intelligence algorithms. The geometry model enables to display the parameter relationships are adequate to requirements of the system approach. The objective character of the elements of the models and high degree of formalization which facilitate the use of the mathematical methods are advantages of these models. At the same time the geometric images are easily interpreted in physiological and clinical terms. The polyparametric modeling is an object oriented tool possessed advances functional facilities and some principal features.

Analysis of P-Systems under a Multiagent Systems Perspective

Membrane computing is a recent area that belongs to natural computing. This field works on computational models based on nature's behavior to process the information. Recently, numerous models have been developed and implemented with this purpose. P-systems are the structures which have been defined, developed and implemented to simulate the behavior and the evolution of membrane systems which we find in nature. What we show in this paper is an application capable to simulate the P-systems based on a multiagent systems (MAS) technology. The main goal we want to achieve is to take advantage of the inner qualities of the multiagent systems. This way we can analyse the proper functioning of any given p-system. When we observe a P-system from a different perspective, we can be assured that it is a particular case of the multiagent systems. This opens a new possibility, in the future, to always evaluate the P-systems in terms of the multiagent systems technology.

Подход к Программированию Агентов в Мультиагентных Системах

Рассмотрены методы спецификации протоколов взаимодействия агентов в мультиагентных системах на языке ПРАЛУ параллельных алгоритмов логического управления, который обладает средствами для представления последовательности состояний диалога, приема и отправки сообщений. Показано, что описание поведения агентов на языке ПРАЛУ позволяет моделировать поведение мультиагентной системы целиком. Предложена методология программирования агентов ПРАЛУ, использующая двухблочную архитектуру: блок синхронизации и функциональный блок. Оригинальной компонентой этой методологии является средство автоматической трансляции блока синхронизации по описанию на ПРАЛУ.

Complex Protection System of Metadata-based Distributed Information Systems

A description of architecture and approaches to the implementation of a protection system of metadatabased adaptable information systems is suggested. Various protection means are examined. The system described is a multilevel complex based on a multiagent system combining IDS functional abilities with structure and logics protection means.

Emotions and a Prior Knowledge Representation in Artificial General Intelligence

In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

An Ontology-based Approach to Student Skills in Multiagent e-Learning Systems

The main idea of our approach is that the domain ontology is not only the instrument of learning but an object of examining student skills. We propose for students to build the domain ontology of examine discipline and then compare it with etalon one. Analysis of student mistakes allows to propose them personalized recommendations and to improve the course materials in general. For knowledge interoperability we apply Semantic Web technologies. Application of agent-based technologies in e-learning provides the personification of students and tutors and saved all users from the routine operations.

Diagnostic Systems in Medicine as Personal Intellectual Tooling

The standards of diagnostic systems formation in medicine based on modeling expert’s “means of action” in form of illegible trees of solution-making taking into consideration the criteria of credibility and usefulness have been suggested. The fragments of “applied” trees at diagnosing infectious and urological diseases have been considered as well. The possibilities of modern tooling theory usage for decision-making during creation of artificial intelligence systems have been discussed.

Decision–making Support Systems as Personal Intellectual Device of a Decision–maker

The problems of the cognitive development of subject “perception” are discussed in the thesis: from the object being studied and means of action till the single system “subject – modus operandi of subject – object”. Problems of increasing adequacy of models of “live” nature are analyzed. The concept of developing decisionmaking support systems as expert systems to decision-making support systems as personal device of a decisionmaker is discussed. The experience of the development of qualitative prediction on the basis of polyvalent dependences, represented by a decision tree, which realizes the concept of “plural subjective determinism”, is analyzed. The examples of applied systems prediction of ecological-economic and social processes are given. The ways of their development are discussed.

Analogous Reasoning and Case-based Reasoning for Intelligent Decision Support Systems

Methods of analogous reasoning and case-based reasoning for intelligent decision support systems are considered. Special attention is drawn to methods based on a structural analogy that take the context into account. This work was supported by RFBR (projects 02-07-90042, 05-07-90232).

A Proposed Structure of Knowledge-Based Hybrid Intelligent Systems for Sophisticated Environments

The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure. One possible structure is proposed in order to form a basis for intelligent system that would be able to operate in complex environments. The basic elements of the proposed structure have found their implemented in software system. This software system is shortly presented in the paper. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are sketched.