完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Yin, Peng-Yeng | |
dc.contributor.author | Cheng, Yung-Pin | |
dc.contributor.author | Yeh, Chung-Chao | |
dc.contributor.author | Shao, B.M. | |
dc.date.accessioned | 2009-08-23T04:41:19Z | |
dc.date.accessioned | 2020-05-25T06:38:03Z | - |
dc.date.available | 2009-08-23T04:41:19Z | |
dc.date.available | 2020-05-25T06:38:03Z | - |
dc.date.issued | 2006-10-24 | |
dc.date.submitted | 2002-12-18 | |
dc.identifier.uri | http://dspace.lib.fcu.edu.tw/handle/2377/2306 | - |
dc.description.abstract | In a distributed system, it is important to find an assignment of program modules to processors such that system cost is minimized or system throughput is maximized. Researchers have proposed serveral versions of formulation to this problem. Howerver, most of the versions proposed are NP-complete, and thus finding the exact solutions is computationally intractable. In this paper, we propose a genetic algorithm and a reinforcement learning algorithm to find the near-optimal module assignment. We present the computational evidence of the two algorithms with a set of simulated data. The direction of furture research is suggested according to the experimental results. | |
dc.description.sponsorship | 東華大學,花蓮縣 | |
dc.format.extent | 20p. | |
dc.format.extent | 160273 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | zh_TW | |
dc.relation.ispartofseries | 2002 ICS會議 | |
dc.subject | Module assignment problem | |
dc.subject | distributed system | |
dc.subject | genetic algorithms | |
dc.subject | reinforcement learning | |
dc.subject.other | Artificial Intelligence | |
dc.title | Computational Evidence on Genetic Algorithms and Reinforcement Learning Algorithms for Module | |
分類: | 2002年 ICS 國際計算機會議 |
文件中的檔案:
檔案 | 描述 | 大小 | 格式 | |
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ce07ics002002000320.PDF | 156.52 kB | Adobe PDF | 檢視/開啟 |
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