Cover Image

Moving Out: Physically-grounded Human-AI Collaboration

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kang, Xuhui, Lee, Sung-Wook, Liu, Haolin, Wang, Yuyan, Kuo, Yen-Ling
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generative Multi-Agent Collaboration in Embodied AI: A Systematic Review
by: Wu, Di, et al.
Published: (2025)

Towards Interpretable Renal Health Decline Forecasting via Multi-LMM Collaborative Reasoning Framework
by: Wu, Peng-Yi, et al.
Published: (2025)

Incorporating Human Flexibility through Reward Preferences in Human-AI Teaming
by: Bhambri, Siddhant, et al.
Published: (2023)

pAI/MSc: ML Theory Research with Humans on the Loop
by: Abdelmoneum, Mahmoud, et al.
Published: (2026)

ThinkTank: A Framework for Generalizing Domain-Specific AI Agent Systems into Universal Collaborative Intelligence Platforms
by: Surabhi, Praneet Sai Madhu, et al.
Published: (2025)

Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning
by: Tang, Shuo, et al.
Published: (2024)

Thought Communication in Multiagent Collaboration
by: Zheng, Yujia, et al.
Published: (2025)

GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space
by: Wang, Wentao, et al.
Published: (2026)

Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems
by: Wang, Zhao, et al.
Published: (2025)

Shaping Zero-Shot Coordination via State Blocking
by: Kang, Mingu, et al.
Published: (2026)

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning
by: Lee, Sunwoo, et al.
Published: (2026)

Disaster Management in the Era of Agentic AI Systems: A Vision for Collective Human-Machine Intelligence for Augmented Resilience
by: Li, Bo, et al.
Published: (2025)

Investigating Relational State Abstraction in Collaborative MARL
by: Utke, Sharlin, et al.
Published: (2024)

MasHost Builds It All: Autonomous Multi-Agent System Directed by Reinforcement Learning
by: Yang, Kuo, et al.
Published: (2025)

Solving Collaborative Dec-POMDPs with Deep Reinforcement Learning Heuristics
by: Soffair, Nitsan
Published: (2022)

Skill-Aligned Fairness in Multi-Agent Learning for Collaboration in Healthcare
by: Ekpo, Promise Osaine, et al.
Published: (2025)

Training Generalizable Collaborative Agents via Strategic Risk Aversion
by: Qu, Chengrui, et al.
Published: (2026)

MADQRL: Distributed Quantum Reinforcement Learning Framework for Multi-Agent Environments
by: Sawaika, Abhishek, et al.
Published: (2026)

Multi-Agent Path Finding via Offline RL and LLM Collaboration
by: Atasever, Merve, et al.
Published: (2025)

Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing
by: Bruns, Ralf, et al.
Published: (2024)

OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration
by: Li, Shijun, et al.
Published: (2025)

MAC: Masked Agent Collaboration Boosts Large Language Model Medical Decision-Making
by: Peng, Zhihao, et al.
Published: (2025)

The Law of Multi-Model Collaboration: Scaling Limits of Model Ensembling for Large Language Models
by: Lu, Dakuan, et al.
Published: (2025)

Planner Matters! An Efficient and Unbalanced Multi-agent Collaboration Framework for Long-horizon Planning
by: Wu, Wenyi, et al.
Published: (2026)

Learning to Communicate and Collaborate in a Competitive Multi-Agent Setup to Clean the Ocean from Macroplastics
by: Siedler, Philipp Dominic
Published: (2023)

A Comprehensive Review of AI Agents: Transforming Possibilities in Technology and Beyond
by: Qu, Xiaodong, et al.
Published: (2025)

Kaleidoscope: Learnable Masks for Heterogeneous Multi-agent Reinforcement Learning
by: Li, Xinran, et al.
Published: (2024)

Aligning Compound AI Systems via System-level DPO
by: Wang, Xiangwen, et al.
Published: (2025)

MAGIC-MASK: Multi-Agent Guided Inter-Agent Collaboration with Mask-Based Explainability for Reinforcement Learning
by: Maliha, Maisha, et al.
Published: (2025)

M3HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
by: Wang, Ziyan, et al.
Published: (2025)

MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation
by: Lin, Qiushi, et al.
Published: (2024)

Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective
by: Raj, Ritik, et al.
Published: (2025)

Learning to Cooperate with Humans using Generative Agents
by: Liang, Yancheng, et al.
Published: (2024)

Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation
by: Kong, Lingkai, et al.
Published: (2025)

Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning
by: He, Zijian, et al.
Published: (2025)

AI Metropolis: Scaling Large Language Model-based Multi-Agent Simulation with Out-of-order Execution
by: Xie, Zhiqiang, et al.
Published: (2024)

TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
by: Lee, Hayeong, et al.
Published: (2026)

Hybrid Agentic AI and Multi-Agent Systems in Smart Manufacturing
by: Farahani, Mojtaba A., et al.
Published: (2025)

AutoSurrogate: An LLM-Driven Multi-Agent Framework for Autonomous Construction of Deep Learning Surrogate Models in Subsurface Flow
by: Liu, Jiale, et al.
Published: (2026)

Bounded Coupled AI Learning Dynamics in Tri-Hierarchical Drone Swarms
by: Bychkov, Oleksii
Published: (2026)