AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Interventional Separation Selection (ISS) is introduced, which repeatedly queries the true system with an admissible intervention on which the surviving candidate models disagree, discards the candidates the outcome contradicts, and stops once no intervention within a cost bound separates the survivors.
Bayesian Chronicle Agents is introduced, a minimal belief layer separating what an agent believes from how it speaks, and it is shown that prescribed $\kappa$ remains recoverable after the language round-trip, with perfect rank-order recovery across all four models.
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