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Journal Biomedical Radioelectronics №6 for 2016 г.
Article in number:
The analysis of statistical model of behaviour of the virtual medical organisation as multi-agent systems
Authors:
V.A. Antipov - Dr.Sc. (Eng.), Professor, Department of Information-Measurement and Biomedical Engineering, Ryazan State Radio Engineering University. E-mail: ParfAnt@rambler.ru
O.V. Antipov - Ph.D. (Eng.), Associate Professor, Department of Chair of Computing and Applied Mathematics, Ryazan State Radio Engineering University. E-mail: oleg@anegmetex.com
A.U. Alexandrov - Magister, Lecturer, Department of Chair of Computing and Applied Mathematics, Ryazan State Radio Engineering University. E-mail: Pronic32@yandex.ru
A.A. Kozlov - Magister, Lecturer, Department of Chair of Computing and Applied Mathematics, Ryazan State Radio Engineering University. E-mail: Kozlov.andrey.143@mail.ru
Abstract:
With the changing landscape of business world, cooperation between the enterprises is the only way to stay on the edge of com-petition. Cooperation enables enterprises to share skills, costs, access to one another-s markets and resources and, at the same time, decrease the risk of investments. Supported with the rapid development of information technologies, virtual organization has the potentials to be the future way of enterprise cooperation and electronic business. This paper investigated the challenges and obstacles that we are still facing. We proposed a negotiation protocol for automatic formation of a virtual organization. We have studied the decision making of individual agent in a multi-dimensional negotiation process. The partner selection process is another issue that we have focused on, we presented a RBFS algorithm to find the optimal membership for the virtual organization. This solution we applied to Virtual Company may not be adequate for a large number of agents and bids, some sort of heuristics or filters are needed for the screening of bids in order to reduce the complexity. We have incorporated the motivational quantities framework for the task selection process so that agents can make rational decision during their operation. We presented a utility mapping function that can model the agent-s preference, promise and penalty policy of the organization. We adapted a statistical model that allows us to predict and analyze the agent-s behavior and the influence on the organization utility. We have also attempted to study of the agent-s local control - how the utility mapping function of the MQ affects the local time/resource allocation and the agent-s overall utility achievement. Though we have gained a big picture view of virtual organization through this study, we also find there are areas where further studies are needed. For example, we have not explored how the agent make decision in the initial bidding process, how the agent should decide whether to bid and how to bid. Analytical work also needs to be done in the statistical model to study how to adjust the parameter in the mapping function in order to optimize some organizational objectives. These, of course, would lead us to our future work.
Pages: 70-81
References
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