4 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Partner-Aware Hierarchical Skill Discovery for Robust Human-AI Collaboration
Adnan Ahmad, Bahareh Nakisa, Mohammad Naim Rastgoo
Multi-agent collaboration, especially in human-AI teaming, requires agents that can adapt to novel partners with diverse and dynamic behaviors. Conventional Deep Hierarchical Reinf…
Adaptive Human-AI Coordination via Hierarchical Action Disentanglement
Adnan Ahmad, Bahareh Nakisa, Mohammad Naim Rastgoo
Human-AI collaboration requires agents that can adapt to diverse partner behaviors and skill levels while remaining robust to unseen partners. Existing methods often collapse to a…
Adaptive XAI in High Stakes Environments: Modeling Swift Trust with Multimodal Feedback in Human AI Teams
Nishani Fernando, Bahareh Nakisa, Adnan Ahmad +1
Effective human-AI teaming heavily depends on swift trust, particularly in high-stakes scenarios such as emergency response, where timely and accurate decision-making is critical.…
BCR-DRL: Behavior- and Context-aware Reward for Deep Reinforcement Learning in Human-AI Coordination
Xin Hao, Bahareh Nakisa, Mohmmad Naim Rastgoo +1
Deep reinforcement Learning (DRL) offers a powerful framework for training AI agents to coordinate with human partners. However, DRL faces two critical challenges in human-AI coord…