The abstract claims α-potential analysis of asymmetric network games, with 2α-Nash convergence guarantees for two algorithms and α controlled by network asymmetry; the attached full text is an unrelated paper, so verification is impossible.
Behavioral Communities and the Atomic Structure of Networks
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abstract
When people prefer to coordinate their behaviors with their friends -- e.g., choosing whether to adopt a new technology, to protest against a government, to attend university -- divisions within a social network can sustain different behaviors in different parts of the network. We define a society's `behavioral communities' via its network's `atoms': groups of people who adopt the same behavior in every equilibrium. We analyze how the atoms change with the intensity of the peer effects, and characterize the atoms in a prominent class of network models. We show that using knowledge of atoms to seed the diffusion of a behavior significantly increases diffusion compared to seeding based on standard community detection algorithms. We also show how to use observed behaviors to estimate the intensity of peer effects.
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cs.GT 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
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Asymmetric Network Games: $\alpha$-Potential Function and Learning
The abstract claims α-potential analysis of asymmetric network games, with 2α-Nash convergence guarantees for two algorithms and α controlled by network asymmetry; the attached full text is an unrelated paper, so verification is impossible.