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.
A simple model of herd behavior
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2025 2verdicts
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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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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.