arXiv Machine Learning September 7, 2026 By Fatemeh Saberi Khomami, Julita Vassileva

Online Change-point Detection for Cooperative Multi-Agent Reinforcement Learning

Read the original on arXiv Machine Learning →

The paper introduces Patterns of Past Rewards (PPR), a lightweight, algorithm‑agnostic online change‑point detector for cooperative multi‑agent reinforcement learning. PPR smooths agents’ return streams, highlights recent changes, and applies a statistical drift detector to flag significant shifts. Experiments in a custom Speaker‑Listener environment show that PPR balances detection speed and alarm stability, outperforming both a smoothed‑return baseline and a raw‑return detector.

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