Developing methods and means of situational modeling
The main theoretical academic findings that were expected included:
1. A set of mathematical and simulation models describing the processes of collective actions in a distributed multi-agent environment.
2. Modern service-oriented architecture and implementation of prototypes of situational modeling method of studying complex socio-economic systems.
3. New mathematical models and solution methods for the multi-criteria problems of political choice and insurance activity, implemented in the form of algorithms within the system of situational modeling.
Information services have become the main tool of designing and implementing innovative transformations in modern economy and management. Taking into account the rising importance of information services, the researchers identify two defining specifics in the prospects for world economic development. First, a sustainable move towards establishing a service-oriented economy. Second, the rapid growth of information economies in size and importance within the national economies of developed countries.
One of the specifics of the current state of affairs in this branch of studies is the rapid development of situational modeling and intellectual data mining technologies. Business applications and decision-making support systems are the most important and promising area for using these technologies. The possibilities of situational modeling integrated with the means of intellectual data mining are best implemented within systems supporting business decision-making. These systems open new possibilities to analysts, researchers and decision makers – company managers and directors.
The complexity and variety of situational modeling system types and intellectual data mining algorithms require a specific end-user interface and operating principles for modeling and situation analysis in specific areas. All world ICT majors have special research units that work in this area.
At the moment, research into social dynamics phenomena uses functional and structural models. At the same time, one of the most promising areas in theoretic and applied studies of complex social systems is multi-aspect mathematical and information modeling in the form of distributed simulation systems based on the interaction paradigm of individual-based systems or, more frequently, agents.
During the design, development and evolution of these multi-agent simulation systems that model different situations, an academic task emerges of creating new fundamental principles of information interaction among various types of agents that comprise the situation model. An efficient solution to this problem requires the rejection of the “closed world” model and forces researchers to concentrate on such problems as meta-data representation and formal multi-aspect modeling of agents’ particular perceptions about the composition and behavior of the subject field, the properties and interfaces of complex software and hardware systems to achieve semantic interaction of distributed components, consistent and holistic application of various formal methods of semantics and pragmatics knowledge acquisition and transformation.