Incorporating Human Flexibility through Reward Preferences in Human-AI Teaming
Fuente:
arXiv
Saved in:
| Main Authors: | Bhambri, Siddhant, Verma, Mudit, Biswas, Upasana, Murthy, Anil, Kambhampati, Subbarao |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Who is Helping Whom? Analyzing Inter-dependencies to Evaluate Cooperation in Human-AI Teaming
by: Biswas, Upasana, et al.
Published: (2025)
by: Biswas, Upasana, et al.
Published: (2025)
Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?
by: Verma, Mudit, et al.
Published: (2024)
by: Verma, Mudit, et al.
Published: (2024)
Do Cognitively Interpretable Reasoning Traces Improve LLM Performance?
by: Bhambri, Siddhant, et al.
Published: (2025)
by: Bhambri, Siddhant, et al.
Published: (2025)
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation
by: Bhambri, Siddhant, et al.
Published: (2025)
by: Bhambri, Siddhant, et al.
Published: (2025)
On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models
by: Verma, Mudit, et al.
Published: (2024)
by: Verma, Mudit, et al.
Published: (2024)
LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks
by: Kambhampati, Subbarao, et al.
Published: (2024)
by: Kambhampati, Subbarao, et al.
Published: (2024)
Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning via Incorporating Generalized Human Expertise
by: Wu, Xuefei, et al.
Published: (2025)
by: Wu, Xuefei, et al.
Published: (2025)
Extracting Heuristics from Large Language Models for Reward Shaping in Reinforcement Learning
by: Bhambri, Siddhant, et al.
Published: (2024)
by: Bhambri, Siddhant, et al.
Published: (2024)
Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards
by: Verma, Shresth, et al.
Published: (2024)
by: Verma, Shresth, et al.
Published: (2024)
Moving Out: Physically-grounded Human-AI Collaboration
by: Kang, Xuhui, et al.
Published: (2025)
by: Kang, Xuhui, et al.
Published: (2025)
pAI/MSc: ML Theory Research with Humans on the Loop
by: Abdelmoneum, Mahmoud, et al.
Published: (2026)
by: Abdelmoneum, Mahmoud, et al.
Published: (2026)
Human Implicit Preference-Based Policy Fine-tuning for Multi-Agent Reinforcement Learning in USV Swarm
by: Kim, Hyeonjun, et al.
Published: (2025)
by: Kim, Hyeonjun, et al.
Published: (2025)
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)
by: Li, Bo, et al.
Published: (2025)
Local Coherence or Global Validity? Investigating RLVR Traces in Math Domains
by: Samineni, Soumya Rani, et al.
Published: (2025)
by: Samineni, Soumya Rani, et al.
Published: (2025)
Learning to Cooperate with Humans using Generative Agents
by: Liang, Yancheng, et al.
Published: (2024)
by: Liang, Yancheng, et al.
Published: (2024)
Talk Freely, Execute Strictly: Schema-Gated Agentic AI for Flexible and Reproducible Scientific Workflows
by: Strickland, Joel, et al.
Published: (2026)
by: Strickland, Joel, et al.
Published: (2026)
Human-compatible driving partners through data-regularized self-play reinforcement learning
by: Cornelisse, Daphne, et al.
Published: (2024)
by: Cornelisse, Daphne, et al.
Published: (2024)
COSAC: Counterfactual Credit Assignment in Sequential Cooperative Teams
by: Deshmukh, Shripad, et al.
Published: (2026)
by: Deshmukh, Shripad, et al.
Published: (2026)
Hierarchical Imitation Learning of Team Behavior from Heterogeneous Demonstrations
by: Seo, Sangwon, et al.
Published: (2025)
by: Seo, Sangwon, et al.
Published: (2025)
Hindsight PRIORs for Reward Learning from Human Preferences
by: Verma, Mudit, et al.
Published: (2024)
by: Verma, Mudit, et al.
Published: (2024)
Goal-Oriented Multi-Agent Reinforcement Learning for Decentralized Agent Teams
by: Du, Hung, et al.
Published: (2025)
by: Du, Hung, et al.
Published: (2025)
Learning the Preferences of a Learning Agent
by: Sadek, Karim Abdel, et al.
Published: (2026)
by: Sadek, Karim Abdel, et al.
Published: (2026)
Value Internalization: Learning and Generalizing from Social Reward
by: Rong, Frieda, et al.
Published: (2024)
by: Rong, Frieda, et al.
Published: (2024)
When Is Diversity Rewarded in Cooperative Multi-Agent Learning?
by: Amir, Michael, et al.
Published: (2025)
by: Amir, Michael, et al.
Published: (2025)
Learn as Individuals, Evolve as a Team: Multi-agent LLMs Adaptation in Embodied Environments
by: Li, Xinran, et al.
Published: (2025)
by: Li, Xinran, et al.
Published: (2025)
ToMCAT: Theory-of-Mind for Cooperative Agents in Teams via Multiagent Diffusion Policies
by: Sequeira, Pedro, et al.
Published: (2025)
by: Sequeira, Pedro, et al.
Published: (2025)
Reward-Independent Messaging for Decentralized Multi-Agent Reinforcement Learning
by: Yoshida, Naoto, et al.
Published: (2025)
by: Yoshida, Naoto, et al.
Published: (2025)
Multi-Agent Reinforcement Learning with a Hierarchy of Reward Machines
by: Zheng, Xuejing, et al.
Published: (2024)
by: Zheng, Xuejing, et al.
Published: (2024)
M3HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
by: Wang, Ziyan, et al.
Published: (2025)
by: Wang, Ziyan, et al.
Published: (2025)
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
by: Gundawar, Atharva, et al.
Published: (2024)
by: Gundawar, Atharva, et al.
Published: (2024)
Achieving Optimal Tissue Repair Through MARL with Reward Shaping and Curriculum Learning
by: Khan, Muhammad Al-Zafar, et al.
Published: (2025)
by: Khan, Muhammad Al-Zafar, et al.
Published: (2025)
Improve Value Estimation of Q Function and Reshape Reward with Monte Carlo Tree Search
by: Li, Jiamian
Published: (2024)
by: Li, Jiamian
Published: (2024)
Mathematical Framework for Custom Reward Functions in Job Application Evaluation using Reinforcement Learning
by: Jain, Shreyansh, et al.
Published: (2025)
by: Jain, Shreyansh, et al.
Published: (2025)
Can Vibe Coding Beat Graduate CS Students? An LLM vs. Human Coding Tournament on Market-driven Strategic Planning
by: Danassis, Panayiotis, et al.
Published: (2025)
by: Danassis, Panayiotis, et al.
Published: (2025)
Offline Risk-sensitive RL with Partial Observability to Enhance Performance in Human-Robot Teaming
by: Angelotti, Giorgio, et al.
Published: (2024)
by: Angelotti, Giorgio, et al.
Published: (2024)
Flexible Swarm Learning May Outpace Foundation Models in Essential Tasks
by: Samadi, Moein E., et al.
Published: (2025)
by: Samadi, Moein E., et al.
Published: (2025)
LERO: LLM-driven Evolutionary framework with Hybrid Rewards and Enhanced Observation for Multi-Agent Reinforcement Learning
by: Wei, Yuan, et al.
Published: (2025)
by: Wei, Yuan, et al.
Published: (2025)
Large Language Model-Based Reward Design for Deep Reinforcement Learning-Driven Autonomous Cyber Defense
by: Mukherjee, Sayak, et al.
Published: (2025)
by: Mukherjee, Sayak, et al.
Published: (2025)
Compositional Coordination for Multi-Robot Teams with Large Language Models
by: Huang, Zhehui, et al.
Published: (2025)
by: Huang, Zhehui, et al.
Published: (2025)
Conformal Set-based Human-AI Complementarity with Multiple Experts
by: Paat, Helbert, et al.
Published: (2025)
by: Paat, Helbert, et al.
Published: (2025)
Similar Items
-
Who is Helping Whom? Analyzing Inter-dependencies to Evaluate Cooperation in Human-AI Teaming
by: Biswas, Upasana, et al.
Published: (2025) -
Theory of Mind abilities of Large Language Models in Human-Robot Interaction : An Illusion?
by: Verma, Mudit, et al.
Published: (2024) -
Do Cognitively Interpretable Reasoning Traces Improve LLM Performance?
by: Bhambri, Siddhant, et al.
Published: (2025) -
Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillation
by: Bhambri, Siddhant, et al.
Published: (2025) -
On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models
by: Verma, Mudit, et al.
Published: (2024)