METHODS OF AGENTS CONTROL IN MULTI-AGENT EXPERT SYSTEM


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In the article we discuss the user models interacting with distributed network resource, where every user has a correlated agent, as well as on the methods of multi-agent expert system control.

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The administration of distributed network resources requires solving tasks, concerned with the complexity of resource-to-user interaction organization. To solve the set task [1] the following multi-agent expert system (fig. 1) has been developed. To organize interaction between users and distributed network resource on a basis of the developed multi-agent expert system model we will consider the following models of agent’s behavior coordination [2–6]: 1. Game-theory modes – solve the tasks of selection solutions in conditions of equivocality and conflict, which if followed, allow the constructing of rule sets and conversations, permitting agents to achieve equilibrium agreements. 2. Models of collective behavior for automats – are based on constructing conversation rules and protocols in tasks, which are characterized by a large quantity of simple interactions with indeterminate characteristics. 3. Models of collective behavior planning reveal methods of agent behavior planning (centralized, partially centralized, distributed) for the purpose of making decisions regarding the selection of self-actions in the process of implementing the plans’ coordination. 4. Models based on BDI-architecture – apply axiomatical methods of the game theory and the artificial intellect’s logical paradigm. The task of the agentscoordination behavior consists in coordinating the output results in the knowledge bases of these agents, obta
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Об авторах

O. V. Aripova

A. N. Guschin

Список литературы

  1. Aripova O. Models of Interaction between User and Distributed Network Resource: Research and information magazine. Innovations. SPb. : JSC “TRANSFER”, 2009.
  2. Andreychikov A., Andreychikova O. Intelligent Information Systems : the Textbook. М. : Finance and statistics, 2006. P. 424.
  3. Gavrilova T., Khoroshevskiy V. Intelligent Systems Knowledgebases. SPb. : Piter, 2001.
  4. Gushin A. Basic Concepts of Personal-Centered Information Systems Development / Voenmeh. Baltic State Technical University Bull. SPb. : “Sot” printing establishment, 2008. P. 34–44.
  5. Laurier J.-L. Artificial Intelligence Systems: transl. from the French. M. : Mir, 1991. P. 568.
  6. Rassel S., Norwig P. Artificial Intelligence: Modern Approach. M. : Williams, 2006. P. 1048.
  7. Yasnitskiy L. Artificial Intelligence Guide-book : Study guide for students of inst. of tertiary education. M. : Academia, 2005. P. 176.

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© Aripova O.V., Guschin A.N., 2010

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