Intelligent Multi-Agent Fuzzy Control System Under Uncertainty

Abstract

The traditional control systems are a set of hardware and software infrastructure domain and qualified personnel to facilitate the functions of analysis, planning, decision-making, management and coordination of business processes. Human interaction with the components of these systems is done using a specified in advance script dialogue menu, mainly based on human intellect and unproductive use of navigation. This approach doesn't lead to making qualitative decision and effective control, where the situations and processes cannot be structured in advance. Any dynamic changes in the controlled business process make it necessary to modify the script dialogue. This circumstance leads to a redesign of the components of the entire control system. In the autonomous Fuzzy Control System, where the situations are unknown in advance, fuzzy structured and artificial intelligence is crucial, the redesign described above is impossible. To solve this problem, we propose the data, information and knowledge based technology of creation Situational, Intelligent Multi-agent Control System, which interacts with users and/ or agent systems in natural and other languages, utilizing the principles of Situational Control and Fuzzy Logic theories, Artificial Intelligence, Linguistics, Knowledge Base technologies and others. The proposed technology is defined by a) methods of situational fuzzy control of data, information and knowledge, b) modelling of fuzzy logic inference, c) generalization and explanation of knowledge, d) fuzzy dialogue control, e) machine translation, f) fuzzy decision-making, g) planning and h) fuzzy control of organizational unit in real-time under uncertainty, fuzzy conditions, heterogeneous domains, multi-lingual communication in Fuzzy Environment.