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\iteman{io-port 05916884}
\itemau{Wu, Yu; Zhang, Yu}
\itemti{Pattern analysis in social networks with dynamic connections.}
\itemso{Salerno, John (ed.) et al., Social computing, behavioral-cultural modeling and prediction. 4th international conference, SBP 2011, College Park, MD, USA, March 29--31, 2011. Proceedings. Berlin: Springer (ISBN 978-3-642-19655-3/pbk). Lecture Notes in Computer Science 6589, 163-171 (2011).}
\itemab
Summary: In this paper, we explore how decentralized local interactions of autonomous agents in a network relate to collective behaviors. Most existing work in this area models social network in which agent relations are fixed; instead, we focus on dynamic social networks where agents can rationally adjust their neighborhoods based on their individual interests. We propose a new connection evaluation rule called the Highest Weighted Reward (HWR) rule, with which agents dynamically choose their neighbors in order to maximize their own utilities based on the rewards from previous interactions. Our experiments show that in the 2-action pure coordination game, our system will stabilize to a clustering state where all relationships in the network are rewarded with the optimal payoff. Our experiments also reveal additional interesting patterns in the network.
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\itemut{Social Network; Dynamic Network; Pattern Analysis}
\itemli{doi:10.1007/978-3-642-19656-0\_25}
\end