Výsledky vyhledávání - "Chen, Qiliang"

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Resource Governance in Networked Systems via Integrated Variational Autoencoders and Reinforcement Learning

We introduce a framework that integrates variational autoencoders (VAE) with reinforcement learning (RL) to balance system performance and resource usage in multi-agent systems by dynamically adjusting network structures over time. A key innovation o

Externí odkaz: http://arxiv.org/abs/2410.23393

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Adaptive Network Intervention for Complex Systems: A Hierarchical Graph Reinforcement Learning Approach

Autor: Chen, Qiliang, Heydari, Babak

Effective governance and steering of behavior in complex multi-agent systems (MAS) are essential for managing system-wide outcomes, particularly in environments where interactions are structured by dynamic networks. In many applications, the goal is

Externí odkaz: http://arxiv.org/abs/2410.23396

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Instigating Cooperation among LLM Agents Using Adaptive Information Modulation

Autor: Chen, Qiliang, Ilami, Sepehr, Lore, Nunzio, Heydari, Babak

This paper introduces a novel framework combining LLM agents as proxies for human strategic behavior with reinforcement learning (RL) to engage these agents in evolving strategic interactions within team environments. Our approach extends traditional

Externí odkaz: http://arxiv.org/abs/2409.10372

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