AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper introduces HarnessEvolve, a self-evolving framework that learns from reference trajectories to achieve reliable agent self-evolution, and overcomes credit assignment failure by generating reference trajectories and aligning failed executions against them to extract error signals.
JANUS is a plug-and-play infill module that extracts a local Jacobian from the recent evaluation trace, and gives the best mean cost on 1135-dimensional UAV path planning and improves SMS-EMOA/AGE-MOEA2 hosts on 12/38 multi-objective tasks with zero significant regressions.
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