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Found 6 papers, 1 papers with code
Bootstrapping Linear Models for Fast Online Adaptation in Human-Agent Collaboration
Initializing policies to maximize performance with unknown partners can be achieved by bootstrapping nonlinear models using imitation learning over large, offline datasets.
VoicePilot: Harnessing LLMs as Speech Interfaces for Physically Assistive Robots
Physically assistive robots present an opportunity to significantly increase the well-being and independence of individuals with motor impairments or other forms of disability who are unable to complete activities of daily living.
Coordination with Humans via Strategy Matching
Human and robot partners increasingly need to work together to perform tasks as a team.
Reasoning about Counterfactuals to Improve Human Inverse Reinforcement Learning
We propose to incorporate the learner's current understanding of the robot's decision making into our model of human IRL, so that a robot can select demonstrations that maximize the human's understanding.
Towards Rich, Portable, and Large-Scale Pedestrian Data Collection
Recently, pedestrian behavior research has shifted towards machine learning based methods and converged on the topic of modeling pedestrian interactions.
DReyeVR: Democratizing Virtual Reality Driving Simulation for Behavioural & Interaction Research
We present DReyeVR, an open-source VR based driving simulator platform designed with behavioural and interaction research priorities in mind.
