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Emergence and evolution of agent-bas...

Yu, Bin.

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Emergence and evolution of agent-based referral networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Emergence and evolution of agent-based referral networks./
作者:	Yu, Bin.
面頁冊數:	110 p.
附註:	Source: Dissertation Abstracts International, Volume: 63-04, Section: B, page: 1935.
Contained By:	Dissertation Abstracts International63-04B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3048940
ISBN:	0493633537

Emergence and evolution of agent-based referral networks.
Yu, Bin.

Emergence and evolution of agent-based referral networks. - 110 p.

Source: Dissertation Abstracts International, Volume: 63-04, Section: B, page: 1935.

Thesis (Ph.D.)--North Carolina State University, 2002.

Numerous studies have shown that interpersonal communication acts as an important channel for gathering information. But if we wish to rely on interpersonal communication, we still need to figure out how to determine the right person to ask. Usually we cannot find the potential expert(s) directly, and we need some assistance from our friends or friends' friends to locate them. The phenomenon of Six Degrees of Separation indicates that it is possible to use some intelligent software agents, who can interpret the links between people and follow only the relevant one, to find the desired experts quickly.

ISBN: 0493633537Subjects--Topical Terms:

626642
Computer Science.

Emergence and evolution of agent-based referral networks.
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502 $a Thesis (Ph.D.)--North Carolina State University, 2002.
520 $a Numerous studies have shown that interpersonal communication acts as an important channel for gathering information. But if we wish to rely on interpersonal communication, we still need to figure out how to determine the right person to ask. Usually we cannot find the potential expert(s) directly, and we need some assistance from our friends or friends' friends to locate them. The phenomenon of Six Degrees of Separation indicates that it is possible to use some intelligent software agents, who can interpret the links between people and follow only the relevant one, to find the desired experts quickly.
520 $a A computational model of agent-based referral networks was proposed to assist and simplify the users to find potential experts for a specified topic in a person-to-person social network, in which each user is assigned a software agent, and software agents help automate the process by a series of "referral chains". Unlike most previous approaches, our architecture is fully distributed and includes agents who preserve the privacy and autonomy of their users. These agents learn models of each other in terms of expertise (ability to produce correct domain answers), and sociability (ability to produce accurate referrals). We study this framework experimentally to see the effects that the different variables have on each other and the efficiency of the referral networks.
520 $a Furthermore, a social mechanism of reputation management was proposed to help agents (users) avoid interaction with undesirable participants in the referral networks. The mathematical theory of evidence is used to represent and propagate the reputation information in a referral network. Our approach adjusts the ratings of agents based on their observations as well the testimony from others. Moreover, we conducted several experiments to study the reputation management in different settings. Social mechanisms are even more important when some centralized reputation management mechanisms, i.e., trusted third parties, are not available. Our specific approach to reputation management leads to a decentralized society in which agents help each other weed out undesirable players.
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