M
Matthew Marge
Researcher at United States Army Research Laboratory
Publications - 47
Citations - 1089
Matthew Marge is an academic researcher from United States Army Research Laboratory. The author has contributed to research in topics: Robot & Human–robot interaction. The author has an hindex of 14, co-authored 45 publications receiving 920 citations. Previous affiliations of Matthew Marge include United States Naval Research Laboratory & Stony Brook University.
Papers
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Proceedings ArticleDOI
Consequences and Factors of Stylistic Differences in Human-Robot Dialogue
Stephanie M. Lukin,Kimberly A. Pollard,Claire Bonial,Matthew Marge,Cassidy Henry,Ron Artstein,David Traum,Clare R. Voss +7 more
TL;DR: This paper identifies stylistic differences in instruction-giving observed in a corpus of human-robot dialogue, and correlations were found between style differences and individual user variation, trust, and interaction experience with the robot.
Posted Content
A Research Platform for Multi-Robot Dialogue with Humans
Matthew Marge,Stephen M. Nogar,Cory J. Hayes,Stephanie M. Lukin,Jesse Bloecker,Eric Holder,Clare R. Voss +6 more
TL;DR: This flexible language and robotic platform takes advantage of existing tools for speech recognition and dialogue management that are compatible with new domains, and implements an inter-agent communication protocol (tactical behavior specification), where verbal instructions are encoded for tasks assigned to the appropriate robot.
Posted Content
Towards Preference Learning for Autonomous Ground Robot Navigation Tasks.
Cory J. Hayes,Matthew Marge +1 more
TL;DR: The work in progress to modify a general model for robot navigation behaviors in an exploration task on a per-user basis using preference-based reinforcement learning to allow an autonomous agent to learn from sustained dialogue with a human teammate as opposed to one-off instructions.
Proceedings Article
How should agents ask questions for situated learning? an annotated dialogue corpus
TL;DR: The Human-Robot Dialogue Learning (HuRDL) corpus as mentioned in this paper is a dialogue corpus collected in an online interactive virtual environment in which human participants play the role of a robot performing a collaborative tool-organization task.
Proceedings ArticleDOI
DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents
Ziqiao Ma,B. VanDerPloeg,Cristian-Paul Bara,Hu Yidong,Eui-In Kim,Felix Gervits,Matthew Marge,Joyce Y. Chai +7 more
TL;DR: Dialogue On the ROad To Handle Irregular Events ( DOROTHIE) is introduced, a novel interactive simulation platform that en-ables the creation of unexpected situations on the basis of end-to-end models to support empirical studies on situated communication with autonomous driving agents.