AI Agent - arXivDaily 专题

2307.05004 2023-07-12 cs.AI cs.LG cs.MA 88%

Control as Probabilistic Inference as an Emergent Communication Mechanism in Multi-Agent Reinforcement Learning

Tomoaki Nakamura, Akira Taniguchi, Tadahiro Taniguchi

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2004.11145 2023-07-10 cs.LG cs.AI cs.MA stat.ML 88%

F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning

Wenhao Li, Bo Jin, Xiangfeng Wang, Junchi Yan, Hongyuan Zha

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 75 pages, 10 figures, JMLR camera ready

2307.03119 2023-07-07 cs.AI cs.LG cs.MA 88%

Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance

Yuchen Fang, Zhenggang Tang, Kan Ren, Weiqing Liu, Li Zhao, Jiang Bian, Dongsheng Li, Weinan Zhang, Yong Yu, Tie-Yan Liu

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted in KDD 2023; The website is at https://seqml.github.io/marl4fin

2307.00552 2023-07-04 cs.LG cs.AI cs.CY cs.MA 88%

Adaptive reinforcement learning of multi-agent ethically-aligned behaviours: the QSOM and QDSOM algorithms

Rémy Chaput, Olivier Boissier, Mathieu Guillermin

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 30 pages, 7 figures, 7 tables

2306.10640 2023-07-04 cs.NE cs.AI cs.LG cs.MA 88%

Evolving Strategies for Competitive Multi-Agent Search

Erkin Bahceci, Riitta Katila, Risto Miikkulainen

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2306.14683 2023-06-27 cs.AI cs.LG eess.SP 88%

Multi-Agent Deep Reinforcement Learning for Dynamic Avatar Migration in AIoT-enabled Vehicular Metaverses with Trajectory Prediction

Junlong Chen, Jiawen Kang, Minrui Xu, Zehui Xiong, Dusit Niyato, Chuan Chen, Abbas Jamalipour, Shengli Xie

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2305.06446 2023-06-27 cs.LG cs.AI cs.MA 88%

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation

Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments Published at the 40th International Conference on Machine Learning ( ICML 2023 )

2306.11846 2023-06-22 cs.AI cs.LG cs.MA stat.ME 88%

Discovering Causality for Efficient Cooperation in Multi-Agent Environments

Rafael Pina, Varuna De Silva, Corentin Artaud

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2306.10134 2023-06-21 cs.LG cs.AI cs.MA 88%

Dynamic Size Message Scheduling for Multi-Agent Communication under Limited Bandwidth

Qingshuang Sun, Denis Steckelmacher, Yuan Yao, Ann Nowé, Raphaël Avalos

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2006.10822 2023-06-21 cs.LG cs.AI math.OC stat.ML 88%

Cooperative Multi-Agent Reinforcement Learning with Partial Observations

Yan Zhang, Michael M. Zavlanos

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2211.07882 2023-06-19 cs.AI cs.LG cs.MA cs.RO 88%

Explainable Action Advising for Multi-Agent Reinforcement Learning

Yue Guo, Joseph Campbell, Simon Stepputtis, Ruiyu Li, Dana Hughes, Fei Fang, Katia Sycara

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2301.01919 2023-06-13 cs.MA cs.AI cs.LG 88%

Scalable Communication for Multi-Agent Reinforcement Learning via Transformer-Based Email Mechanism

Xudong Guo, Daming Shi, Wenhui Fan

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted by IJCAI 2023

2212.08230 2023-06-12 cs.AI cs.LG cs.MA cs.RO 88%

An Energy-aware and Fault-tolerant Deep Reinforcement Learning based approach for Multi-agent Patrolling Problems

Chenhao Tong, Aaron Harwood, Maria A. Rodriguez, Richard O. Sinnott

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2102.03479 2023-06-09 cs.LG cs.AI cs.MA 88%

Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning

Jian Hu, Siyang Jiang, Seth Austin Harding, Haibin Wu, Shih-wei Liao

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted by ICLR BlogTrack 2023

2302.04445 2023-06-08 cs.MA cs.AI cs.LG 88%

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems

Chanyoung Park, Won Joon Yun, Jae Pyoung Kim, Tiago Koketsu Rodrigues, Soohyun Park, Soyi Jung, Joongheon Kim

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 16 pages, 9 figures

2306.03314 2023-06-07 cs.AI cs.LG cs.MA 88%

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Yashar Talebirad, Amirhossein Nadiri

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2306.01920 2023-06-06 cs.MA cs.AI cs.GT cs.LG 88%

Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

Dingyang Chen, Qi Zhang

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2210.11942 2023-06-05 cs.GT cs.AI cs.LG cs.MA 88%

Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning

Matthias Gerstgrasser, David C. Parkes

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2306.00212 2023-06-02 cs.LG cs.AI cs.SY eess.SY math.OC 88%

Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning

Dongsheng Ding, Xiaohan Wei, Zhuoran Yang, Zhaoran Wang, Mihailo R. Jovanović

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 59 pages, a full version of the main paper in the 5th Annual Conference on Learning for Dynamics and Control

2103.13026 2023-05-30 cs.LG cs.AI cs.MA 88%

The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication

Xing Xu, Rongpeng Li, Zhifeng Zhao, Honggang Zhang

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2305.17141 2023-05-30 cs.MA cs.AI cs.LG 88%

Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning

Zeng Da

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2301.06889 2023-05-30 cs.LG cs.AI cs.MA 88%

Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State

Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Journal ref Transactions on Machine Learning Research, May 2023

2305.10548 2023-05-19 cs.LG cs.AI cs.MA 88%

Discovering Individual Rewards in Collective Behavior through Inverse Multi-Agent Reinforcement Learning

Daniel Waelchli, Pascal Weber, Petros Koumoutsakos

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2302.02180 2023-05-18 cs.MA cs.AI cs.LG 88%

Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative Multi-Agent Reinforcement Learning

Zhiwei Xu, Bin Zhang, Dapeng Li, Guangchong Zhou, Zeren Zhang, Guoliang Fan

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 20 pages, 17 figures and 4 tables

2305.05566 2023-05-10 cs.LG cs.AI cs.MA 88%

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

Adam Michalski, Filippos Christianos, Stefano V. Albrecht

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2111.02827 2023-05-03 cs.CL cs.LG 88%

Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel

Kevin Eloff, Okko Räsänen, Herman A. Engelbrecht, Arnu Pretorius, Herman Kamper

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.CL、cs.LG

Comments 10 pages, 3 figures, 6 tables

2304.10124 2023-04-21 cs.AI cs.LG cs.MA 88%

Mastering Asymmetrical Multiplayer Game with Multi-Agent Asymmetric-Evolution Reinforcement Learning

Chenglu Sun, Yichi Zhang, Yu Zhang, Ziling Lu, Jingbin Liu, Sijia Xu, Weidong Zhang

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

2212.05331 2023-04-21 cs.LG cs.AI 88%

Effects of Spectral Normalization in Multi-agent Reinforcement Learning

Kinal Mehta, Anuj Mahajan, Pawan Kumar

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments Accepted at IJCNN-2023

2304.08493 2023-04-19 cs.MA cs.AI cs.LG cs.RO 88%

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications

Chanyoung Park, Haemin Lee, Won Joon Yun, Soyi Jung, Joongheon Kim

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

Comments 2 pages, 4 figures

2304.07948 2023-04-18 cs.AI cs.DC cs.LG 88%

Sustainable AIGC Workload Scheduling of Geo-Distributed Data Centers: A Multi-Agent Reinforcement Learning Approach

Siyue Zhang, Minrui Xu, Wei Yang Bryan Lim, Dusit Niyato

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI、cs.LG

1. 多智能体 14815 篇

Control as Probabilistic Inference as an Emergent Communication Mechanism in Multi-Agent Reinforcement Learning

F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning

Learning Multi-Agent Intention-Aware Communication for Optimal Multi-Order Execution in Finance

Adaptive reinforcement learning of multi-agent ethically-aligned behaviours: the QSOM and QDSOM algorithms

Evolving Strategies for Competitive Multi-Agent Search

Multi-Agent Deep Reinforcement Learning for Dynamic Avatar Migration in AIoT-enabled Vehicular Metaverses with Trajectory Prediction

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation

Discovering Causality for Efficient Cooperation in Multi-Agent Environments

Dynamic Size Message Scheduling for Multi-Agent Communication under Limited Bandwidth

Cooperative Multi-Agent Reinforcement Learning with Partial Observations

Explainable Action Advising for Multi-Agent Reinforcement Learning

Scalable Communication for Multi-Agent Reinforcement Learning via Transformer-Based Email Mechanism

An Energy-aware and Fault-tolerant Deep Reinforcement Learning based approach for Multi-agent Patrolling Problems

Rethinking the Implementation Tricks and Monotonicity Constraint in Cooperative Multi-Agent Reinforcement Learning

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning

Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning

The Gradient Convergence Bound of Federated Multi-Agent Reinforcement Learning with Efficient Communication

Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning

Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State

Discovering Individual Rewards in Collective Behavior through Inverse Multi-Agent Reinforcement Learning

Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative Multi-Agent Reinforcement Learning

SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning

Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel

Mastering Asymmetrical Multiplayer Game with Multi-Agent Asymmetric-Evolution Reinforcement Learning

Effects of Spectral Normalization in Multi-agent Reinforcement Learning

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications

Sustainable AIGC Workload Scheduling of Geo-Distributed Data Centers: A Multi-Agent Reinforcement Learning Approach