The paper introduces the Distinguish-or-Homogenize principle, where an agent can either spend resources to differentiate between latent fault models or alter the system state so that the remaining models share a common acceptable policy, eliminating further diagnosis. This leads to the Last-Chance Policy Identification (LCPI) framework, which evaluates correctness at the reached state rather than the initial one, and defines the Last Identifiable Margin (LIM) as the boundary between distinguishing and homogenizing. For deterministic diagnostic graphs, an Exact-LIM recursion is provided, while for noisy finite-horizon recovery the authors propose Risk-Budgeted Compatibility Planning (RBCP), which searches a compatibility-aware frontier under a hard worst-case failure constraint, demonstrating improved risk-feasible recovery in microservice and MiniGrid scenarios.
By Yibo Guo, Xiaodan Wang
arXiv:2609.14422v1 Announce Type: new
Abstract: Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. Whi...
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By Hanwool Lee, Dasol Choi, Bokyeong Kim, Haon Park, Seung Geun Kim
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arXiv:2607. 19338v1 Announce Type: new Abstract: Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect answer.
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