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arXiv · 2609.27365

Anchor and Perturb: Lazy Agent Remediation by Exploration Injection

Chengxi Zhong·Yongzhe Chang
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Abstract

Anchor and Perturb (AnP) is a lightweight framework that resolves multi-agent coordination failures by decoupling exploratory variance injection from recurrent manifold stability. Existing remediation strategies predominantly alter mixing network architectures or enforce simultaneous exploration across the collective, which inevitably precipitates severe temporal-difference penalties in non-monotonic reward spaces. Specifically, AnP isolates underperforming lazy agents and injects an asymmetric exploratory pulse into targeted coordinates whilst anchoring converged teammates to nominal greedy exploitation. Empirical telemetry benchmarks demonstrate that AnP successfully rescues collapsed joint policies (recovering from a 5% evaluation win rate nadir back to 85%) and facilitates escape from suboptimal coordination plateaus, sustaining peak win rates of 90% without requiring structural network modifications.

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Chengxi Zhong, Yongzhe Chang. 2026-09-23. Anchor and Perturb: Lazy Agent Remediation by Exploration Injection. https://arxiv.org/abs/2609.27365

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