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Autores principales: Barzegaran, Mohammadreza, Han, Kemeng, Jafarkhani, Hamid
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2605.14121
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author Barzegaran, Mohammadreza
Han, Kemeng
Jafarkhani, Hamid
author_facet Barzegaran, Mohammadreza
Han, Kemeng
Jafarkhani, Hamid
contents This paper studies the synthesis of control policies for heterogeneous and interconnected multi-agent systems that collaborate through data exchange over a communication network to minimize a collective cost. We propose a distributed encoded corrective double actor-critic framework that integrates a novel message-passing mechanism. Existing methods assume noise-free and delay-free access to the global or partial states and overlook the fact that the global states, though noisy and delayed, can be progressively reconstructed and refined over time. In contrast, this work explicitly models communication sampling asynchrony, delay, and link noise based on the network configuration. The proposed message-passing mechanism characterizes timing and information flow to refine and time shift global state information, which is then used to incrementally correct the Q-networks. The double Q-network design mitigates overestimation bias, while the shared encoder coupling the actor-critic networks captures inter-agent dependencies. We evaluate our approach in multiple test cases, demonstrate its effectiveness over various baselines, and provide a numerical regret analysis.
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id arxiv_https___arxiv_org_abs_2605_14121
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle An Encoded Corrective Double Deep Q-Networks for Multi-Agent Control Systems
Barzegaran, Mohammadreza
Han, Kemeng
Jafarkhani, Hamid
Signal Processing
Systems and Control
This paper studies the synthesis of control policies for heterogeneous and interconnected multi-agent systems that collaborate through data exchange over a communication network to minimize a collective cost. We propose a distributed encoded corrective double actor-critic framework that integrates a novel message-passing mechanism. Existing methods assume noise-free and delay-free access to the global or partial states and overlook the fact that the global states, though noisy and delayed, can be progressively reconstructed and refined over time. In contrast, this work explicitly models communication sampling asynchrony, delay, and link noise based on the network configuration. The proposed message-passing mechanism characterizes timing and information flow to refine and time shift global state information, which is then used to incrementally correct the Q-networks. The double Q-network design mitigates overestimation bias, while the shared encoder coupling the actor-critic networks captures inter-agent dependencies. We evaluate our approach in multiple test cases, demonstrate its effectiveness over various baselines, and provide a numerical regret analysis.
title An Encoded Corrective Double Deep Q-Networks for Multi-Agent Control Systems
topic Signal Processing
Systems and Control
url https://arxiv.org/abs/2605.14121