Authors:
Andrey Smirnov
1
;
Renat Khabibulin
1
;
Nikolay Topolski
1
and
Denis Tarakanov
2
Affiliations:
1
The State Fire Academy of EMERCOM of Russia, 129366, B. Galushkina 4, Moscow and Russia
;
2
The Ivanovo State Fire Academy of EMERCOM of Russia, 153040, Stroiteley 33, Ivanovo and Russia
Keyword(s):
Multi-agent Systems, Multi-agent Management, Multi-level Procedure, Long-term Planning Tasks, Shannon Entropy, Decision Support Systems.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Scheduling and Planning
;
Software Engineering
;
Symbolic Systems
Abstract:
Algorithmization and program implementation of theoretical positions of multi-agent analysis of resource allocation variants to ensure fire safety were conducted. The informational decision support system was developed, within which variations of resource allocation in a multi-agent management system are offered. The feature of the developing informational system from similar is an ability of approximations of expert’s opinion accounting multi-level procedure of variation’s analysis in a multi-agent management system. The multi-level procedure of variation’s analysis allows to approximate preference of the management centre more completely and, therefore, to reduce the subjectivity of the process of making decisions on resource allocation to ensure fire safety. The procedure includes two main stages: on the first stage component-goals are distributed by sets; on the second stage we get the ranking according to the preference of the management centre. Using quantitative measures of th
e Shannon entropy it is proved that the offered multi-level procedure of variations analysis in multi-agent management system allows to approximate the preference of the management centre more completely in comparison with known methods of variations of resource allocation analysis in long-term planning tasks.
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