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AquaMend: Minimal Re-probing and Conditional Rollback for Latent-Belief Failures in Embodied Agents

2026-09-24 03:39:48
Yufan Liu, Shang Luo, Yang Liu, Haoxuan Jia, Feiyu Han, Qian Li, Chen Li, Yingguang Yang, Chongyang Zhang, Hao Zheng, Kefu Xu, Bin Chong

Abstract

Physical changes or sensing errors can invalidate embodied agents' task-relevant beliefs. AquaMend compares re-probing, rollback, and supported continuation on a probe-belief-action graph under an expected-loss objective covering sensing, physical recovery, and uncorrected failures. A joint posterior guides a one-step policy with conditional detection-power screening. The per-belief three-way optimum requires independence, separability, and fully resolving probes; the general policy has no global optimality guarantee. Across 32 paired scenarios in a self-constructed simulation benchmark, AquaMend recovers in 28/32 cases and reduces mean complete loss by 21.6% versus restart. Its paired loss difference from decision-theoretic troubleshooting (DTT) is not statistically significant after Holm correction. Against the all-candidate ablation, online decision time decreases by 12.3% overall but increases by 3.4% in the uncovered late stage.

Abstract (translated)

URL

https://arxiv.org/abs/2609.28973

PDF

https://arxiv.org/pdf/2609.28973.pdf


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