5 citations · 9 across the 5 of their papers we have counts for
5 papers
AAAI SSS-22 Symposium on Closing the Assessment Loop: Communicating Proficiency and Intent in Human-Robot Teaming
Michael Goodrich, Jacob Crandall, Aaron Steinfeld +1
The proposed symposium focuses understanding, modeling, and improving the efficacy of (a) communicating proficiency from human to robot and (b) communicating intent from a human to…
Predicting Plans and Actions in Two-Player Repeated Games
Najma Mathema, Michael A. Goodrich, Jacob W. Crandall
Artificial intelligence (AI) agents will need to interact with both other AI agents and humans. Creating models of associates help to predict the modeled agents' actions, plans, an…
E-HBA: Using Action Policies for Expert Advice and Agent Typification
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
Past research has studied two approaches to utilise predefined policy sets in repeated interactions: as experts, to dictate our own actions, and as types, to characterise the behav…
An Empirical Study on the Practical Impact of Prior Beliefs over Policy Types
Stefano V. Albrecht, Jacob W. Crandall, Subramanian Ramamoorthy
Many multiagent applications require an agent to learn quickly how to interact with previously unknown other agents. To address this problem, researchers have studied learning algo…
Regulating Highly Automated Robot Ecologies: Insights from Three User Studies
Wen Shen, Alanoud Al Khemeiri, Abdulla Almehrezi +3
Highly automated robot ecologies (HARE), or societies of independent autonomous robots or agents, are rapidly becoming an important part of much of the world's critical infrastruct…