235 citations · 237 across the 6 of their papers we have counts for
6 papers
Designing Behavior Trees from Goal-Oriented LTLf Formulas
Aadesh Neupane, Eric G Mercer, Michael A. Goodrich
Temporal logic can be used to formally specify autonomous agent goals, but synthesizing planners that guarantee goal satisfaction can be computationally prohibitive. This paper sho…
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…
Efficiently Evolving Swarm Behaviors Using Grammatical Evolution With PPA-style Behavior Trees
Aadesh Neupane, Michael A. Goodrich
Evolving swarm behaviors with artificial agents is computationally expensive and challenging. Because reward structures are often sparse in swarm problems, only a few simulations a…
Proceedings of the 2020 Workshop on Assessing, Explaining, and Conveying Robot Proficiency for Human-Robot Teaming
Aaron Steinfeld, Michael Goodrich
This record contains the proceedings of the 2020 Workshop on Assessing, Explaining, and Conveying Robot Proficiency for Human-Robot Teaming, which was held in conjunction with the…
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…
Cooperating with Machines
Jacob W. Crandall, Mayada Oudah, Tennom +7
Since Alan Turing envisioned Artificial Intelligence (AI) [1], a major driving force behind technical progress has been competition with human cognition. Historical milestones have…