31 citations · 57 across the 5 of their papers we have counts for
7 papers
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
Rohan Paleja, Muyleng Ghuy, Nadun Ranawaka Arachchige +2
Recent advances in machine learning have led to growing interest in Explainable AI (xAI) to enable humans to gain insight into the decision-making of machine learning models. Despi…
Towards Sample-efficient Apprenticeship Learning from Suboptimal Demonstration
Letian Chen, Rohan Paleja, Matthew Gombolay
Learning from Demonstration (LfD) seeks to democratize robotics by enabling non-roboticist end-users to teach robots to perform novel tasks by providing demonstrations. However, as…
Heterogeneous Graph Attention Networks for Learning Diverse Communication
Esmaeil Seraj, Zheyuan Wang, Rohan Paleja +3
Multi-agent teaming achieves better performance when there is communication among participating agents allowing them to coordinate their actions for maximizing shared utility. Howe…
Learning from Suboptimal Demonstration via Self-Supervised Reward Regression
Letian Chen, Rohan Paleja, Matthew Gombolay
Learning from Demonstration (LfD) seeks to democratize robotics by enabling non-roboticist end-users to teach robots to perform a task by providing a human demonstration. However,…
Heterogeneous Learning from Demonstration
Rohan Paleja, Matthew Gombolay
The development of human-robot systems able to leverage the strengths of both humans and their robotic counterparts has been greatly sought after because of the foreseen, broad-ran…
Joint Goal and Strategy Inference across Heterogeneous Demonstrators via Reward Network Distillation
Letian Chen, Rohan Paleja, Muyleng Ghuy +1
Reinforcement learning (RL) has achieved tremendous success as a general framework for learning how to make decisions. However, this success relies on the interactive hand-tuning o…