Cover Image

A Roadmap Towards Improving Multi-Agent Reinforcement Learning With Causal Discovery And Inference

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Briglia, Giovanni, Mariani, Stefano, Zambonelli, Franco
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Multiagent Systems Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference
by: Lee, Po-Han, et al.
Published: (2025)

Scaling Multi-Agent Epistemic Planning through GNN-Derived Heuristics
by: Briglia, Giovanni, et al.
Published: (2025)

NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
by: Lu, Haoran, et al.
Published: (2026)

Decentralizing Multi-Agent Reinforcement Learning with Temporal Causal Information
by: Corazza, Jan, et al.
Published: (2025)

Causally-Guided Automated Feature Engineering with Multi-Agent Reinforcement Learning
by: Malarkkan, Arun Vignesh, et al.
Published: (2026)

Towards Fault Tolerance in Multi-Agent Reinforcement Learning
by: Shi, Yuchen, et al.
Published: (2024)

Federated Causal Discovery From Interventions
by: Abyaneh, Amin, et al.
Published: (2022)

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing
by: Jin, Yue, et al.
Published: (2024)

Dynamic Pricing in High-Speed Railways Using Multi-Agent Reinforcement Learning
by: Villarrubia-Martin, Enrique Adrian, et al.
Published: (2025)

CrowdLLM: Building LLM-Based Digital Populations Augmented with Generative Models
by: Lin, Ryan Feng, et al.
Published: (2025)

Estimating counterfactual treatment outcomes over time in complex multiagent scenarios
by: Fujii, Keisuke, et al.
Published: (2022)

Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning
by: Gerstgrasser, Matthias, et al.
Published: (2023)

Redistributing Rewards Across Time and Agents for Multi-Agent Reinforcement Learning
by: Kapoor, Aditya, et al.
Published: (2025)

Reinforced Agent: Inference-Time Feedback for Tool-Calling Agents
by: Ta, Anh, et al.
Published: (2026)

Goal-Oriented Multi-Agent Reinforcement Learning for Decentralized Agent Teams
by: Du, Hung, et al.
Published: (2025)

Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning
by: Huh, Dom, et al.
Published: (2024)

Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning
by: Liu, Shunyu, et al.
Published: (2022)

BenchMARL: Benchmarking Multi-Agent Reinforcement Learning
by: Bettini, Matteo, et al.
Published: (2023)

Multi-Agent Car Parking using Reinforcement Learning
by: Tanner, Omar
Published: (2022)

Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox
by: Yin, Qiyue, et al.
Published: (2022)

Reinforcement Networks: novel framework for collaborative Multi-Agent Reinforcement Learning tasks
by: Kryzhanovskiy, Maksim, et al.
Published: (2025)

Hierarchical Policy-Gradient Reinforcement Learning for Multi-Agent Shepherding Control of Non-Cohesive Targets
by: Covone, Stefano, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey
by: Hady, Mohamad A., et al.
Published: (2025)

Adaptability in Multi-Agent Reinforcement Learning: A Framework and Unified Review
by: Hu, Siyi, et al.
Published: (2025)

FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
by: Li, Wenzhe, et al.
Published: (2024)

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
by: Jiang, Jiechuan, et al.
Published: (2024)

Challenges in Credit Assignment for Multi-Agent Reinforcement Learning in Open Agent Systems
by: Abadi, Alireza Saleh, et al.
Published: (2025)

CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making
by: Minelli, Giovanni, et al.
Published: (2023)

Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning
by: Castagna, Alberto
Published: (2025)

Reward-Independent Messaging for Decentralized Multi-Agent Reinforcement Learning
by: Yoshida, Naoto, et al.
Published: (2025)

Turn-based Multi-Agent Reinforcement Learning Model Checking
by: Gross, Dennis
Published: (2025)

The Composite Task Challenge for Cooperative Multi-Agent Reinforcement Learning
by: Li, Yurui, et al.
Published: (2025)

Dynamic Sight Range Selection in Multi-Agent Reinforcement Learning
by: Liao, Wei-Chen, et al.
Published: (2025)

Coordination Matters: Evaluation of Cooperative Multi-Agent Reinforcement Learning
by: Cardei, Maria Ana, et al.
Published: (2026)

Group-Aware Coordination Graph for Multi-Agent Reinforcement Learning
by: Duan, Wei, et al.
Published: (2024)

Selective Reincarnation: Offline-to-Online Multi-Agent Reinforcement Learning
by: Formanek, Claude, et al.
Published: (2023)

Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
by: Gao, Riqiang, et al.
Published: (2024)

LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning
by: Bae, Sangjun, et al.
Published: (2026)

Trust-based Consensus in Multi-Agent Reinforcement Learning Systems
by: Fung, Ho Long, et al.
Published: (2022)

Putting Data at the Centre of Offline Multi-Agent Reinforcement Learning
by: Formanek, Claude, et al.
Published: (2024)