Research on multi-agent system based trust model of partner selection of virtual enterprise

Author(s):  
Wang Shixian ◽  
Wei Siying
2014 ◽  
Vol 36 ◽  
pp. 367-372 ◽  
Author(s):  
B. Lotfi Sadigh ◽  
F. Arikan ◽  
A.M. Ozbayoglu ◽  
H.O. Unver ◽  
S.E. Kilic

Author(s):  
Gehao Lu ◽  
Joan Lu

This chapter focuses on the testing for a complete systematic neural trust model developed previously based on the trust learning algorithms, trust estimation algorithm and reputation mechanisms. The focus is to describe the detailed design of the model and explain the rationales behind the model design. The purpose is to evaluate the proposed neural trust model from different aspects and analyze the results of the evaluations. Experiments have been conducted. Results are presented and discussed. Finally, based on the analysis and comparison of acquired results, conclusions are drawn.


Author(s):  
MIHAELA ULIERU ◽  
RAINER UNLAND

In today's world, it is of utterly importance for enterprises to react in a timely and flexible way to upcoming complex market demands. One solution is given by the concept of virtual enterprise and enterprise alliances, respectively. In order to function efficiently and flexibly such enterprises need to be deeply integrated. Based on previous work combining the concepts of virtual enterprises, holonic organizations and multi-agent systems to support such deep integration, the paper discusses in detail how well-suiting partners and contributors for a given (bunch of) task(s) can be found using today's state-of-the-art technologies. Mapping an enterprise alliance onto a multi-agent system is enabled by a methodology equipping each agent with the ability to deal and consider its own goals (goals of the unit it represents) as well as the goals of the unit in which it is integrated (the higher level unit).


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