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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liu Ping Hu Yongtong Yan Yuhong Zheng Danian Yang Shiyuan |
| Copyright Year | 1997 |
| Description | Author affiliation: Dept. of Autom., Tsinghua Univ., Beijing, China (Liu Ping) |
| Abstract | Multiagent systems have been widely used in concurrent engineering. However, most multi-agent tasks have high complexity. Optimal solutions of them are nearly intractable due to the heavy load of communication and large complexity of knowledge exchanges. In this paper, we extend the agent structure in our previous work. Rather than using common multi-agent diagram, we use stochastic search techniques such as genetic algorithms (GAs) to explore the solutions. Moreover, we also add counter proposals to speed up the searching process. Experimental results about designing a gear pump are satisfying, which turn out that the combination of GAs (modified to adapt to counter proposals) and Multiagent Systems can considerably speed up the convergence process, and at the same time, guarantee the best globe solution. |
| Starting Page | 891 |
| Ending Page | 895 |
| File Size | 457134 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780342534 |
| DOI | 10.1109/ICIPS.1997.672936 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1997-10-28 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Process design Multiagent systems Automation Stochastic processes Turning Concurrent engineering Proposals Biological cells Genetic algorithms Counting circuits |
| Content Type | Text |
| Resource Type | Article |
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