AI Agent - arXivDaily 专题

2206.01888 2023-03-09 cs.LG cs.AI cs.CR cs.GT 88%

Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning

Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

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

2303.01936 2023-03-06 cs.LG cs.AI cs.MA 88%

Multi-Agent Adversarial Training Using Diffusion Learning

Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed

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

2301.11153 2023-03-06 cs.LG cs.AI cs.MA 88%

Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning

Sriram Ganapathi Subramanian, Matthew E. Taylor, Kate Larson, Mark Crowley

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

Comments Paper to appear in AAMAS 2023, London, UK

2302.06606 2023-03-03 cs.LG cs.AI cs.GT cs.MA stat.ML 88%

Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation

Yuanhao Wang, Qinghua Liu, Yu Bai, Chi Jin

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

2205.15434 2023-03-03 cs.LG cs.AI cs.GT cs.MA 88%

A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems

Oliver Slumbers, David Henry Mguni, Stephen Marcus McAleer, Stefano B. Blumberg, Jun Wang, Yaodong Yang

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

2302.14276 2023-03-01 cs.LG cs.AI cs.MA 88%

On the Role of Emergent Communication for Social Learning in Multi-Agent Reinforcement Learning

Seth Karten, Siva Kailas, Huao Li, Katia Sycara

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

Comments 14 pages, 5 figures

2302.12232 2023-02-24 cs.LG cs.AI cs.RO 88%

Concept Learning for Interpretable Multi-Agent Reinforcement Learning

Renos Zabounidis, Joseph Campbell, Simon Stepputtis, Dana Hughes, Katia Sycara

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

Comments Accepted to the 6th Conference on Robot Learning (CoRL 2022), Auckland, New Zealand

2301.10993 2023-02-24 cs.LG cs.AI cs.MA 88%

Multi-Agent Congestion Cost Minimization With Linear Function Approximations

Prashant Trivedi, Nandyala Hemachandra

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

Comments Accepted at International Conference on Artificial Intelligence and Statistics (AISTATS) 2023

2211.00801 2023-02-24 cs.LG cs.AI cs.NA math.NA 88%

Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement

Jiachen Yang, Ketan Mittal, Tarik Dzanic, Socratis Petrides, Brendan Keith, Brenden Petersen, Daniel Faissol, Robert Anderson

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

Comments AAMAS 2023. 17 pages, 17 figures

2302.09277 2023-02-21 cs.LG cs.AI cs.MA cs.RO 88%

Promoting Cooperation in Multi-Agent Reinforcement Learning via Mutual Help

Yunbo Qiu, Yue Jin, Lebin Yu, Jian Wang, Xudong Zhang

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

Comments Accepted by 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023)

2302.07493 2023-02-16 cs.LG cs.AI cs.DC 88%

Adaptive incentive for cross-silo federated learning: A multi-agent reinforcement learning approach

Shijing Yuan, Hongze Liu, Hongtao Lv, Zhanbo Feng, Jie Li, Hongyang Chen, Chentao Wu

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

2302.03429 2023-02-08 cs.AI cs.LG cs.MA 88%

Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning

Rundong Wang, Longtao Zheng, Wei Qiu, Bowei He, Bo An, Zinovi Rabinovich, Yujing Hu, Yingfeng Chen, Tangjie Lv, Changjie Fan

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

2302.01199 2023-02-03 cs.NI cs.AI cs.LG 88%

Multi-agent Reinforcement Learning with Graph Q-Networks for Antenna Tuning

Maxime Bouton, Jaeseong Jeong, Jose Outes, Adriano Mendo, Alexandros Nikou

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

Comments 9 pages, 8 figures, to appear in IEEE NOMS 2023

2301.11014 2023-01-27 cs.LG cs.AI cs.CR 88%

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

Yan Lin, Jinming Bao, Yijin Zhang, Jun Li, Feng Shu, Lajos Hanzo

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

Comments 6 pages, 4 figures, IEEE Trans. on Veh. Technol

2002.05233 2023-01-23 cs.LG cs.AI cs.MA stat.ML 88%

Learning Multi-Agent Coordination through Connectivity-driven Communication

Emanuele Pesce, Giovanni Montana

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

Journal ref Machine Learning (December 2022)

2301.08030 2023-01-20 cs.LG cs.AI cs.MA 88%

Multi-Agent Interplay in a Competitive Survival Environment

Andrea Fanti

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

Comments 21 pages, 11 figures, part of a Master's thesis, Sapienza University of Rome, 2022

2301.05334 2023-01-16 cs.LG cs.AI cs.MA 88%

TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems

Matteo Gallici, Mario Martin, Ivan Masmitja

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

Comments Accepted at AAMAS 2023. Code at https://github.com/mttga/pymarl_transformers

2301.04299 2023-01-12 cs.LG cs.AI cs.CR 88%

SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning

Maxwell Standen, Junae Kim, Claudia Szabo

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

2105.15013 2023-01-10 cs.LG cs.AI cs.MA 88%

SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning

Jianhong Wang, Yuan Zhang, Yunjie Gu, Tae-Kyun Kim

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

Comments Accepted paper for NeurIPS 2022

2301.02593 2023-01-09 cs.MA cs.AI cs.LG cs.SY eess.SY 88%

Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads

Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry

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

Comments Presented as an extended abstract at AAMAS 2023

2203.02896 2023-01-03 cs.LG cs.AI cs.MA 88%

Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation

Donghan Xie, Zhi Wang, Chunlin Chen, Daoyi Dong

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

Comments Accepted by IEEE Transactions on Neural Networks, 2022, DOI: 10.1109/TNNLS.2022.3230701

2212.13448 2022-12-29 cs.LG cs.AI cs.MA 88%

Strangeness-driven Exploration in Multi-Agent Reinforcement Learning

Ju-Bong Kim, Ho-Bin Choi, Youn-Hee Han

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

Comments 9 pages, 7 figures

2212.07891 2022-12-16 cs.AI cs.CV cs.LG cs.MA 88%

Emergent Behaviors in Multi-Agent Target Acquisition

Piyush K. Sharma, Erin Zaroukian, Derrik E. Asher, Bryson Howell

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

Comments This article appeared in the news at: https://www.army.mil/article/258408/u_s_army_scientists_invent_a_method_to_characterize_ai_behavior

Journal ref Published in:Proceedings Volume 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV; 1211314 (6 June 2022), SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

2210.12933 2022-12-14 cs.AI cs.LG cs.MA 88%

Multi-Agent Path Finding via Tree LSTM

Yuhao Jiang, Kunjie Zhang, Qimai Li, Jiaxin Chen, Xiaolong Zhu

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

Comments Appear in AAAI23-MAPF

2204.09418 2022-12-08 cs.MA cs.AI cs.LG 88%

Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning

Zhiwei Xu, Dapeng Li, Bin Zhang, Yuan Zhan, Yunpeng Bai, Guoliang Fan

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, 2 tables

2211.17116 2022-12-01 cs.LG cs.AI cs.MA math.OC 88%

Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning

Yizhou Zhang, Guannan Qu, Pan Xu, Yiheng Lin, Zaiwei Chen, Adam Wierman

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

2211.16385 2022-11-30 cs.AR cs.AI cs.LG cs.MA 88%

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration

Srivatsan Krishnan, Natasha Jaques, Shayegan Omidshafiei, Dan Zhang, Izzeddin Gur, Vijay Janapa Reddi, Aleksandra Faust

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

Comments Workshop on ML for Systems at NeurIPS 2022

2211.15414 2022-11-29 cs.AI cs.LG cs.MA cs.RO 88%

Dynamic Collaborative Multi-Agent Reinforcement Learning Communication for Autonomous Drone Reforestation

Philipp Dominic Siedler

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

Comments Deep Reinforcement Learning Workshop at the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)

2208.11510 2022-11-29 quant-ph cs.AI cs.LG cs.MA 88%

Quantum Multi-Agent Meta Reinforcement Learning

Won Joon Yun, Jihong Park, Joongheon Kim

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

Comments (To be) presented at AAAI 2023

2211.11759 2022-11-23 cs.LG cs.AI cs.MA 88%

Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning

Junjie Sheng, Lu Wang, Fangkai Yang, Bo Qiao, Hang Dong, Xiangfeng Wang, Bo Jin, Jun Wang, Si Qin, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang

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 14922 篇

Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning

Multi-Agent Adversarial Training Using Diffusion Learning

Learning from Multiple Independent Advisors in Multi-agent Reinforcement Learning

Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation

A Game-Theoretic Framework for Managing Risk in Multi-Agent Systems

On the Role of Emergent Communication for Social Learning in Multi-Agent Reinforcement Learning

Concept Learning for Interpretable Multi-Agent Reinforcement Learning

Multi-Agent Congestion Cost Minimization With Linear Function Approximations

Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement

Promoting Cooperation in Multi-Agent Reinforcement Learning via Mutual Help

Adaptive incentive for cross-silo federated learning: A multi-agent reinforcement learning approach

Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning

Multi-agent Reinforcement Learning with Graph Q-Networks for Antenna Tuning

Privacy-Preserving Joint Edge Association and Power Optimization for the Internet of Vehicles via Federated Multi-Agent Reinforcement Learning

Learning Multi-Agent Coordination through Connectivity-driven Communication

Multi-Agent Interplay in a Competitive Survival Environment

TransfQMix: Transformers for Leveraging the Graph Structure of Multi-Agent Reinforcement Learning Problems

SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning

SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning

Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads

Depthwise Convolution for Multi-Agent Communication with Enhanced Mean-Field Approximation

Strangeness-driven Exploration in Multi-Agent Reinforcement Learning

Emergent Behaviors in Multi-Agent Target Acquisition

Multi-Agent Path Finding via Tree LSTM

Mingling Foresight with Imagination: Model-Based Cooperative Multi-Agent Reinforcement Learning

Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration

Dynamic Collaborative Multi-Agent Reinforcement Learning Communication for Autonomous Drone Reforestation

Quantum Multi-Agent Meta Reinforcement Learning

Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning