DocumentCode :
2666649
Title :
Quantifying agent strategies under reputation
Author :
Marti, Sergio ; Garcia-Molina, Hector
Author_Institution :
Stanford Univ., CA, USA
fYear :
2005
fDate :
31 Aug.-2 Sept. 2005
Firstpage :
97
Lastpage :
105
Abstract :
Our research proposes a simple buyer/seller game that captures the incentives dictating the interaction between peers in resource trading peer-to-peer networks. We prove that for simple reputation-based buyer strategies, a seller´s decision whether to cheat or not is dependent only on the length of its transaction history, not on the particular actions committed. Given a finite number of transactions, a peer can compute a utility optimal sequence of cooperations and defections. With the limited information provided by many reputation systems, a peer has incentive to defect on a large fraction of its transactions. If temporal information is used, equilibrium is reached when peers predominantly cooperate.
Keywords :
cooperative systems; electronic trading; peer-to-peer computing; transaction processing; agent strategy; cooperative system; peer-to-peer network; reputation-based buyer strategy; transaction processing; utility optimal sequence; Analytical models; Cost accounting; Feedback; Game theory; History; Microeconomics; Nash equilibrium; Peer to peer computing; Protocols; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Peer-to-Peer Computing, 2005. P2P 2005. Fifth IEEE International Conference on
Print_ISBN :
0-7695-2376-5
Type :
conf
DOI :
10.1109/P2P.2005.29
Filename :
1551025
Link To Document :
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