Copertina

A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Satheesh, Anirudh, Powell, Keenan
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Multiagent Systems Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending
di: Satheesh, Anirudh, et al.
Pubblicazione: (2025)

OffLight: An Offline Multi-Agent Reinforcement Learning Framework for Traffic Signal Control
di: Bokade, Rohit, et al.
Pubblicazione: (2024)

A Semi Centralized Training Decentralized Execution Architecture for Multi Agent Deep Reinforcement Learning in Traffic Signal Control
di: Rezaali, Arash, et al.
Pubblicazione: (2025)

Multi-Objective Reinforcement Learning for Large-Scale Mixed Traffic Control
di: Islam, Iftekharul, et al.
Pubblicazione: (2025)

Multi-agent Reinforcement Learning for Cooperative Lane Changing of Connected and Autonomous Vehicles in Mixed Traffic
di: Zhou, Wei, et al.
Pubblicazione: (2021)

Constrained Black-Box Attacks Against Cooperative Multi-Agent Reinforcement Learning
di: Andam, Amine, et al.
Pubblicazione: (2025)

Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL)
di: Mondal, Washim Uddin, et al.
Pubblicazione: (2022)

Large-Scale Mixed-Traffic and Intersection Control using Multi-agent Reinforcement Learning
di: Liu, Songyang, et al.
Pubblicazione: (2025)

Bayesian Critique-Tune-Based Reinforcement Learning with Adaptive Pressure for Multi-Intersection Traffic Signal Control
di: Duan, Wenchang, et al.
Pubblicazione: (2024)

Communication Strategy on Macro-and-Micro Traffic State in Cooperative Deep Reinforcement Learning for Regional Traffic Signal Control
di: Gu, Hankang, et al.
Pubblicazione: (2025)

A Hierarchical Deep Reinforcement Learning Framework for Traffic Signal Control with Predictable Cycle Planning
di: Gu, Hankang, et al.
Pubblicazione: (2025)

Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
di: Hoppe, Heiko, et al.
Pubblicazione: (2023)

MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control
di: Lee, Sunbowen, et al.
Pubblicazione: (2024)

A Reinforcement Learning Approach to Quiet and Safe UAM Traffic Management
di: Murthy, Surya, et al.
Pubblicazione: (2025)

Learning to Communicate in Multi-Agent Reinforcement Learning for Autonomous Cyber Defence
di: Contractor, Faizan, et al.
Pubblicazione: (2025)

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control
di: Zhu, Liwen, et al.
Pubblicazione: (2021)

WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control
di: Monroc, Claire Bizon, et al.
Pubblicazione: (2025)

A Tensor Network Implementation of Multi Agent Reinforcement Learning
di: Howard, Sunny
Pubblicazione: (2024)

A Survey of Multi-Agent Deep Reinforcement Learning with Communication
di: Zhu, Changxi, et al.
Pubblicazione: (2022)

Multi-Agent Craftax: Benchmarking Open-Ended Multi-Agent Reinforcement Learning at the Hyperscale
di: Omari, Bassel Al, et al.
Pubblicazione: (2025)

Focusing Influence Mechanism for Multi-Agent Reinforcement Learning
di: Park, Yisak, et al.
Pubblicazione: (2025)

Trajectory-Class-Aware Multi-Agent Reinforcement Learning
di: Na, Hyungho, et al.
Pubblicazione: (2025)

Double Distillation Network for Multi-Agent Reinforcement Learning
di: Zhou, Yang, et al.
Pubblicazione: (2025)

Generalized Intention Modeling in Multi-Agent Reinforcement Learning
di: Odrowaz-Sypniewski, Mateusz, et al.
Pubblicazione: (2026)

An Initial Introduction to Cooperative Multi-Agent Reinforcement Learning
di: Amato, Christopher
Pubblicazione: (2024)

Fully Independent Communication in Multi-Agent Reinforcement Learning
di: Pina, Rafael, et al.
Pubblicazione: (2024)

Interactive Distillation for Cooperative Multi-Agent Reinforcement Learning
di: Cho, Minwoo, et al.
Pubblicazione: (2026)

Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning
di: Zhang, Yiyao, et al.
Pubblicazione: (2026)

Preference-Guided Learning for Sparse-Reward Multi-Agent Reinforcement Learning
di: Bui, The Viet, et al.
Pubblicazione: (2025)

Learning to Coordinate via Quantum Entanglement in Multi-Agent Reinforcement Learning
di: Gardiner, John, et al.
Pubblicazione: (2026)

Multi-Agent Based Transfer Learning for Data-Driven Air Traffic Applications
di: Deng, Chuhao, et al.
Pubblicazione: (2024)

Quantum Computing and Neuromorphic Computing for Safe, Reliable, and explainable Multi-Agent Reinforcement Learning: Optimal Control in Autonomous Robotics
di: Taghavi, Mazyar, et al.
Pubblicazione: (2024)

GuideLight: "Industrial Solution" Guidance for More Practical Traffic Signal Control Agents
di: Jiang, Haoyuan, et al.
Pubblicazione: (2024)

Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
di: Wang, Xuefeng, et al.
Pubblicazione: (2025)

Stronger-MAS: Multi-Agent Reinforcement Learning for Collaborative LLMs
di: Zhao, Yujie, et al.
Pubblicazione: (2025)

CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning
di: Gupta, Nikunj, et al.
Pubblicazione: (2023)

Events as Triggers for Behavioral Diversity in Multi-Agent Reinforcement Learning
di: Büchi, Hannes, et al.
Pubblicazione: (2026)

Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems
di: Holder, Joshua, et al.
Pubblicazione: (2024)

Hierarchical Lead Critic based Multi-Agent Reinforcement Learning
di: Eckel, David, et al.
Pubblicazione: (2026)

Conservative and Risk-Aware Offline Multi-Agent Reinforcement Learning
di: Eldeeb, Eslam, et al.
Pubblicazione: (2024)