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Neurodynamic programming: a case study of the traveling salesman problem
Ma, Jia1; Yang, Tao1; Hou, Zeng-Guang1; Tan, Min1; Liu, Derong2
刊名NEURAL COMPUTING & APPLICATIONS
2008-08-01
卷号17期号:4页码:347-355
关键词neurodynamic programming temporal difference learning approximate Sarsa traveling salesman problem
英文摘要The paper focuses on the study of solving the large-scale traveling salesman problem (TSP) based on neurodynamic programming. From this perspective, two methods, temporal difference learning and approximate Sarsa, are presented in detail. In essence, both of them try to learn an appropriate evaluation function on the basis of a finite amount of experience. To evaluate their performances, some computational experiments on both the Euclidean and asymmetric TSP instances are conducted. In contrast with the large size of the state space, only a few training sets have been used to obtain the initial results. Hence, the results are acceptable and encouraging in comparisons with some classical algorithms, and further study of this kind of methods, as well as applications in combinatorial optimization problems, is worth investigating.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]ALGORITHM ; SEARCH ; NET
收录类别SCI ; ISTP
语种英语
WOS记录号WOS:000257124100004
公开日期2015-12-24
内容类型期刊论文
源URL[http://ir.ia.ac.cn/handle/173211/9557]  
专题自动化研究所_09年以前成果
作者单位1.Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China
2.Univ Illinois, Dept Elect & Comp Engn, Chicago, IL 60607 USA
推荐引用方式
GB/T 7714
Ma, Jia,Yang, Tao,Hou, Zeng-Guang,et al. Neurodynamic programming: a case study of the traveling salesman problem[J]. NEURAL COMPUTING & APPLICATIONS,2008,17(4):347-355.
APA Ma, Jia,Yang, Tao,Hou, Zeng-Guang,Tan, Min,&Liu, Derong.(2008).Neurodynamic programming: a case study of the traveling salesman problem.NEURAL COMPUTING & APPLICATIONS,17(4),347-355.
MLA Ma, Jia,et al."Neurodynamic programming: a case study of the traveling salesman problem".NEURAL COMPUTING & APPLICATIONS 17.4(2008):347-355.
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