Framework of agent-based intelligence system with two-stage decision-making process for distributed dynamic scheduling |
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Affiliation: | 1. Trend Micro CDC, PR China;2. State Key Laboratory for Novel Software Technology, Nanjing University, 163 Xianlin Avenue Nanjing, Jiangsu 210023\nPR China;1. Dept. of Civil and Env. Engineering, Islamic University of Technology, Board Bazar, Gazipur 1704, Bangladesh;2. Dept. of Civil Engineering, National Univ. of Singapore, 117576 Singapore, Singapore;1. Rolls-Royce@NTU Corp Lab, Nanyang Technological University, Singapore;2. Rolls-Royce Singapore Pte Ltd, Singapore;3. School of Computer Science and Engineering, Nanyang Technological University, Singapore |
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Abstract: | The advent of multiagent systems, a branch of distributed artificial intelligence, introduced a new approach to problem solving through agents interacting in the problem solving process. In this paper, a collaborative framework of a distributed agent-based intelligence system is addressed to control and resolve dynamic scheduling problem of distributed projects for practical purposes. If any delay event occurs, the self-interested activity agent, the major agent for the problem solving of dynamic scheduling in the framework, can automatically cooperate with other agents in real time to solve the problem through a two-stage decision-making process: the fuzzy decision-making process and the compensatory negotiation process. The first stage determines which behavior strategy will be taken by agents while delay event occurs, and prepares to next negotiation process; then the compensatory negotiations among agents are opened related with determination of compensations for respective decisions and strategies, to solve dynamic scheduling problem in the second stage. A prototype system is also developed and simulated with a case to validate the problem solving of distributed dynamic scheduling in the framework. |
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