Cover Image

MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Dong, Chen, Zhengzhang, Zhao, Xujiang, Yu, Linlin, Chen, Zhong, He, Yi, Chen, Haifeng, Zhao, Chen
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online Multi-modal Root Cause Identification in Microservice Systems
by: Zheng, Lecheng, et al.
Published: (2024)

Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery
by: Shen, ChengAo, et al.
Published: (2024)

SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search
by: Li, Dong, et al.
Published: (2025)

LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis
by: Zheng, Lecheng, et al.
Published: (2024)

Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement
by: Ying, Wangyang, et al.
Published: (2026)

Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments
by: Lin, Yujie, et al.
Published: (2023)

Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery
by: Darvariu, Victor-Alexandru, et al.
Published: (2023)

Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation
by: Lin, Minhua, et al.
Published: (2024)

Multi-modal Causal Structure Learning and Root Cause Analysis
by: Zheng, Lecheng, et al.
Published: (2024)

Multi-Scenario Combination Based on Multi-Agent Reinforcement Learning to Optimize the Advertising Recommendation System
by: Zhao, Yang, et al.
Published: (2024)

RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection
by: Deng, Chengyuan, et al.
Published: (2024)

Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs
by: Liu, Xuyuan, et al.
Published: (2025)

Co-jump: Cooperative Jumping with Quadrupedal Robots via Multi-Agent Reinforcement Learning
by: Dong, Shihao, et al.
Published: (2026)

Red-Team Multi-Agent Reinforcement Learning for Emergency Braking Scenario
by: Chen, Yinsong, et al.
Published: (2025)

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

ChordPrompt: Orchestrating Cross-Modal Prompt Synergy for Multi-Domain Incremental Learning in CLIP
by: Wang, Zhiyuan, et al.
Published: (2025)

PiFlow: Principle-Aware Scientific Discovery with Multi-Agent Collaboration
by: Pu, Yingming, et al.
Published: (2025)

Diffusion Models for Reinforcement Learning: A Survey
by: Zhu, Zhengbang, et al.
Published: (2023)

POWQMIX: Weighted Value Factorization with Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning
by: Huang, Chang, et al.
Published: (2024)

Learning Future Representation with Synthetic Observations for Sample-efficient Reinforcement Learning
by: Liu, Xin, et al.
Published: (2024)

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

Stratified GRPO: Handling Structural Heterogeneity in Reinforcement Learning of LLM Search Agents
by: Zhu, Mingkang, et al.
Published: (2025)

TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents
by: Lee, Geon, et al.
Published: (2025)

SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training
by: He, Zhongyu, et al.
Published: (2026)

SeaDAG: Semi-autoregressive Diffusion for Conditional Directed Acyclic Graph Generation
by: Zhou, Xinyi, et al.
Published: (2024)

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents
by: Li, Guankai, et al.
Published: (2026)

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning
by: Wang, Qingjun, et al.
Published: (2026)

Knockoff-Guided Feature Selection via A Single Pre-trained Reinforced Agent
by: Wang, Xinyuan, et al.
Published: (2024)

Inverse Reinforcement Learning from Non-Stationary Learning Agents
by: Sivakumar, Kavinayan P., et al.
Published: (2024)

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

Cross-domain Random Pre-training with Prototypes for Reinforcement Learning
by: Liu, Xin, et al.
Published: (2023)

Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach
by: Chen, Yuxuan, et al.
Published: (2024)

DAG-AFL:Directed Acyclic Graph-based Asynchronous Federated Learning
by: Zhang, Shuaipeng, et al.
Published: (2025)

Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
by: Liu, Zeyang, et al.
Published: (2024)

ADORA: Training Reasoning Models with Dynamic Advantage Estimation on Reinforcement Learning
by: Ren, Qingnan, et al.
Published: (2026)

Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning
by: Chen, Xi, et al.
Published: (2025)

Solving Continual Offline Reinforcement Learning with Decision Transformer
by: Huang, Kaixin, et al.
Published: (2024)

LiteGUI: Distilling Compact GUI Agents with Reinforcement Learning
by: Wu, Yubin, et al.
Published: (2026)

Agent Lightning: Train ANY AI Agents with Reinforcement Learning
by: Luo, Xufang, et al.
Published: (2025)

MARS: Co-evolving Dual-System Deep Research via Multi-Agent Reinforcement Learning
by: Chen, Guoxin, et al.
Published: (2025)