Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
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A simple model of herd behavior
3 Pith papers cite this work, alongside 6,561 external citations. Polarity classification is still indexing.
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In a sequential review model, rewarding agreement between first and last report incentivizes early effort when reviews can overturn errors, while rewarding final accuracy works better when reports are copied; the choice hinges on the probability of repairing initial mistakes.
Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.
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Mean-Field Analysis of Latent Variable Process Models on Dynamically Evolving Graphs with Feedback Effects
Characterizes the distributional mean-field limit of co-evolving latent space networks with feedback, including empirical measures and graphon convergence, via a conditional propagation of chaos result.
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Washed Out by the Crowd? Accountability under Sequential Review
In a sequential review model, rewarding agreement between first and last report incentivizes early effort when reviews can overturn errors, while rewarding final accuracy works better when reports are copied; the choice hinges on the probability of repairing initial mistakes.
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A Tutorial on Cognitive Biases in Agentic AI-Driven 6G Autonomous Networks
Randomized Weibull anchors and debiased collective memory with decay and inflection bonuses let agentic AI in 6G cut anchoring, temporal, and confirmation biases, doubling energy savings to 25% and reducing latency by 5x in simulations.