Design of Multi Agent System for Resource Allocation and Monitoring

Design of Multi Agent System for Resource Allocation and Monitoring

Manish Arora (DOEACC Society, India) and M. Syamala Devi (Panjab University, India)
Copyright: © 2012 |Pages: 10
DOI: 10.4018/978-1-4666-1565-6.ch001
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The objective of Resource Allocation and Monitoring System is to make the procedures involved in allocating fund resources to competing clients transparent so that deserving candidates get funds. Proactive and goal directed behaviour of agents make the system transparent and intelligent. This paper presents design of Multi Agent Systems for Resource Allocation and Monitoring using Agent Unified Modelling Language (AUML) and implementation in agent based development tool. At a conceptual level, three agents are identified with their roles and responsibilities. The identified agents, functionalities, and interactions are also included and results show that multi agent technology can be used for effective decision making for resource allocation and monitoring problem.
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In their study, Jenyl Mumpower and Thomas A. Darling (1991) have discussed three procedures that can be used to resolve Resource Allocation Problem. In Incremental Appropriation, resource allocation begins with no allocation and then allocates small resources. The process is repeated until resources are exhausted. In the second procedure, multiple negotiators give different concessions. Resources are moved from one point to another and utility function is checked. In the third procedure, different negotiators assign different weights to different programmes.

Quantification of non-quantitative indicators is important to make decision of allocation (Jin et al., 2008). The non-quantifiable indicators can be measured through fuzzy comprehensive measurement method. Since non-quantifiable indicators are measured by human, whose knowledge and experiences may not be complete and exact. The probabilistic tools are used to deal with such data. This approach is also used to rank employees’ performance using both quantitative and non-quantitative measures.

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