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Robust incentive techniques for peer-to-peer networks
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WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Hidden-action in multi-hop routing
Proceedings of the 6th ACM conference on Electronic commerce
Braess's paradox in large random graphs
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
From Local Behaviors to the Dynamics in an Agent Network
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Strong equilibrium in cost sharing connection games
Proceedings of the 8th ACM conference on Electronic commerce
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Proceedings of the 8th ACM conference on Electronic commerce
The Dangers of Poorly Connected Peers in Structured P2P Networks and a Solution Based on Incentives
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Behavioral experiments in networked trade
Proceedings of the 9th ACM conference on Electronic commerce
MABS'06 Proceedings of the 2006 international conference on Multi-agent-based simulation VII
A many valued representation and propagation of trust and distrust
WILF'05 Proceedings of the 6th international conference on Fuzzy Logic and Applications
A survey and comparison of peer-to-peer overlay network schemes
IEEE Communications Surveys & Tutorials
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In networks, autonomous nodes have action choices along two dimensions: They can forward/process incoming service requests – or not, and they can establish new links and maintain or terminate existing ones. In other words, a node can choose both an action-selection and a link-selection strategy. Nodes in networks are either humans (as in social networks) or agents controlled by humans, so the question how humans forming networks behave is important. Humans behave boundedly rational at times, e.g., game-theoretic predictions do not always hold. This paper investigates the questions whether individuals being nodes in a network find and actually use strategies leading to efficiency (in the economic sense), how exogenous parameters influence behavior, and what are characteristics of the resulting network. We do so by carrying out laboratory experiments with human subjects (120 altogether) who form a network and have those action choices. Our work is different from previous work on P2P systems which lets nodes choose their actions or their links, but not both. Main findings are that link selection increases cooperation and results in optimal payoffs in relative terms. Thus, link selection fosters efficiency.