Cover Image

Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Hyeonjun, Lee, Kanghoon, Park, Junho, Li, Jiachen, Park, Jinkyoo
Format:	Preprint
Published:	2025
Subjects:	Multiagent Systems Artificial Intelligence Machine Learning Robotics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Priority-Aware Multi-Robot Coverage Path Planning
by: Lee, Kanghoon, et al.
Published: (2026)

Cooperative Informative Sensing for Monitoring Dynamic Indoor Environments via Multi-Agent Reinforcement Learning
by: Lee, Kanghoon, et al.
Published: (2026)

Learning Strategy Representation for Imitation Learning in Multi-Agent Games
by: Lei, Shiqi, et al.
Published: (2024)

Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding
by: Tang, Huijie, et al.
Published: (2024)

HiMAP: Learning Heuristics-Informed Policies for Large-Scale Multi-Agent Pathfinding
by: Tang, Huijie, et al.
Published: (2024)

ELA: Exploited Level Augmentation for Offline Learning in Zero-Sum Games
by: Lei, Shiqi, et al.
Published: (2024)

A Local Information Aggregation based Multi-Agent Reinforcement Learning for Robot Swarm Dynamic Task Allocation
by: Lv, Yang, et al.
Published: (2024)

Multi-Agent Dynamic Relational Reasoning for Social Robot Navigation
by: Li, Jiachen, et al.
Published: (2024)

Hierarchical Consensus-Based Multi-Agent Reinforcement Learning for Multi-Robot Cooperation Tasks
by: Feng, Pu, et al.
Published: (2024)

Cooperation and Fairness in Multi-Agent Reinforcement Learning
by: Aloor, Jasmine Jerry, et al.
Published: (2024)

On Swarm Leader Identification using Probing Policies
by: Bachoumas, Stergios E., et al.
Published: (2025)

GenSwarm: Scalable Multi-Robot Code-Policy Generation and Deployment via Language Models
by: Ji, Wenkang, et al.
Published: (2025)

MARFT: Multi-Agent Reinforcement Fine-Tuning
by: Liao, Junwei, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
by: Zhang, Ruiqi, et al.
Published: (2024)

Communication-Free Collective Navigation for a Swarm of UAVs via LiDAR-Based Deep Reinforcement Learning
by: Choi, Myong-Yol, et al.
Published: (2026)

Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning
by: Huang, Zhehui, et al.
Published: (2023)

Distributed Online Planning for Min-Max Problems in Networked Markov Games
by: Tzikas, Alexandros E., et al.
Published: (2024)

SafeDiver: Cooperative AUV-USV Assisted Diver Communication via Multi-agent Reinforcement Learning Approach
by: Deng, Tinglong, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Autonomous Multi-Satellite Earth Observation: A Realistic Case Study
by: Hady, Mohamad A., et al.
Published: (2025)

An Analysis of Constraint-Based Multi-Agent Pathfinding Algorithms
by: Lee, Hannah, et al.
Published: (2025)

Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning
by: Yu, Peihong, et al.
Published: (2024)

Policies over Poses: Reinforcement Learning based Distributed Pose-Graph Optimization for Multi-Robot SLAM
by: Ghanta, Sai Krishna, et al.
Published: (2025)

Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers
by: Krnjaic, Aleksandar, et al.
Published: (2022)

Learning Policies for Dynamic Coalition Formation in Multi-Robot Task Allocation
by: Bezerra, Lucas C. D., et al.
Published: (2024)

Budget Allocation Policies for Real-Time Multi-Agent Path Finding
by: Beck, Raz, et al.
Published: (2025)

Deep Reinforcement Learning for Multi-Agent Coordination
by: Aina, Kehinde O., et al.
Published: (2025)

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

Cross-Modal Navigation with Multi-Agent Reinforcement Learning
by: Liu, Shuo, et al.
Published: (2026)

Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
by: Bettini, Matteo, et al.
Published: (2024)

Local Guidance for Configuration-Based Multi-Agent Pathfinding
by: Arita, Tomoki, et al.
Published: (2025)

Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning
by: Yu, Xin, et al.
Published: (2023)

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning
by: Zhang, Beining, et al.
Published: (2025)

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

ESP: Exploiting Symmetry Prior for Multi-Agent Reinforcement Learning
by: Yu, Xin, et al.
Published: (2023)

R2BC: Multi-Agent Imitation Learning from Single-Agent Demonstrations
by: Mattson, Connor, et al.
Published: (2025)

Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfinding
by: Chung, Jaehoon, et al.
Published: (2023)

Multi-UAV Swarm Obstacle Avoidance Based on Potential Field Optimization
by: Hu, Yendo, et al.
Published: (2025)

Hilbert-Augmented Reinforcement Learning for Scalable Multi-Robot Coverage and Exploration
by: Gurunathan, Tamil Selvan, et al.
Published: (2026)

Learning to Swarm with Knowledge-Based Neural Ordinary Differential Equations
by: Jiahao, Tom Z., et al.
Published: (2021)

Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning
by: Shi, Yuchen, et al.
Published: (2024)