AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper argues that the current main approaches in multi-objective RL (SER and ESR), and successor features, are insufficient, and motivates that this can indeed be the case by an example, leading to a new perspective, and a significant and non-trivial gap in the literature.
This work presents OOD-RL-Bench, a comprehensive and extensible framework designed to evaluate OOD detectors against categories of anomalies injected into RL trajectories, and makes the framework, trained policy checkpoint, and complete results publicly available as a reproducible artefact.
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