Ma4div: Multi-agent reinforcement learning for search result diversification
The objective of search result diversification (SRD) is to ensure that selected documents
cover as many different subtopics as possible. Existing methods primarily utilize a paradigm …
cover as many different subtopics as possible. Existing methods primarily utilize a paradigm …
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
Retrieval-augmented generation (RAG) is extensively utilized to incorporate external,
current knowledge into large language models, thereby minimizing hallucinations. A …
current knowledge into large language models, thereby minimizing hallucinations. A …
Fusion-PSRO: Nash Policy Fusion for Policy Space Response Oracles
For solving zero-sum games involving non-transitivity, a common approach is to maintain
population policies to approximate the Nash Equilibrium (NE). Previous research has shown …
population policies to approximate the Nash Equilibrium (NE). Previous research has shown …
Double Distillation Network for Multi-Agent Reinforcement Learning
Y Zhou, S Wang, W Chen, R Zhang, Z Zhao… - arxiv preprint arxiv …, 2025 - arxiv.org
Multi-agent reinforcement learning typically employs a centralized training-decentralized
execution (CTDE) framework to alleviate the non-stationarity in environment. However, the …
execution (CTDE) framework to alleviate the non-stationarity in environment. However, the …
基于多智能体**化学**的博弈综述
**艺春， 刘泽娇， 洪艺天， 王继超， 王健瑞， **毅， 唐漾 - 自动化学报, 2024 - aas.net.cn
多智能体**化学**作为博弈论, 控制论和多智能体学**的交叉研究领域, 是多智能体系统研究中
的前沿方向, 赋予了智能体在动态多维的复杂环境中通过交互和决策完成多样化任务的能力 …
的前沿方向, 赋予了智能体在动态多维的复杂环境中通过交互和决策完成多样化任务的能力 …
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach
Asynchronous action coordination presents a pervasive challenge in Multi-Agent Systems
(MAS), which can be represented as a Stackelberg game (SG). However, the scalability of …
(MAS), which can be represented as a Stackelberg game (SG). However, the scalability of …