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- W1992848158 abstract "Network games provide a basic framework for studying the diffusion of new ideas or behaviors through a population. In these models, agents decide to adopt a new idea based on optimizing pay-off that depends on the adoption decisions of their neighbors in an underlying network. Assuming such a model, we consider the problem of inferring early adopters or first movers given a snap shot of the adoption state at a given time. We present some results on solving this problem in the low temperature regime. We conclude with a discussion on reducing the complexity of such inference problems for large networks." @default.
- W1992848158 created "2016-06-24" @default.
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- W1992848158 date "2012-10-01" @default.
- W1992848158 modified "2023-09-23" @default.
- W1992848158 title "Spotting trendsetters: Inference for network games" @default.
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- W1992848158 doi "https://doi.org/10.1109/allerton.2012.6483426" @default.
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