AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces FWP (Fragility-Weighted Perplexity), computed from prompt tokens on a reference-instance prefill and calibrated to candidate-instance degradation, and yields a signed reduced-reward score that is KKT-consistent with the LP optimum under optimal prices and primal-feasible tie allocation.
This work proposes an efficient algorithm to achieve regret bound O(K sqrt(T) log T) under concave revenue conditions and O(K^(2/3) T^(2/3) (log T)^(1/2) for the general case, with matching lower bounds confirming optimality.
A Mean-Calibrated Kernel UCB (MCK-UCB) algorithm is proposed that turns each incomplete sales record into a reliable guide for both inventory and price decisions, using data from past rounds with similar market conditions.
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