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

Paper recorded by Signals 4 on 2026-09-04 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.LG · 机器学习 · first seen 2026-09-07

Abstract

Cooperative multi-agent reinforcement learning (MARL) systems rely on past experience for learning coordinated behaviour, but this experience may become unreliable if the environment or task objective changes during training. In such cases, agents first need a way to recognize that the situation has changed before deciding how to adapt. This paper studies online change-point detection for cooperat

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#115 most recent of 215 cs.LG papers we have recorded · ↑ newer: Optimal Rates for Agentic Networked Information Aggregation · ↓ older: LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metr
Cite this page: Online Change-point Detection for Cooperative Multi-Agent Reinforcement Learning: the #115 most recent of 215 cs.LG papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/online-change-point-detection-for-cooperative-multi-agent-reinforcement-learning.html
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