Behavior recognition based on machine learning algorithms for a wireless canine machine interface. - Rita Brugarolas; Robert T. Loftin; Pu Yang; David L. Roberts 001; Barbara L. Sherman; Alper Bozkurt (BSN, 2013)

Improving developer participation rates in surveys. - Edward K. Smith; Robert T. Loftin; Emerson R. Murphy-Hill; Christian Bird; Thomas Zimmermann 001 (CHASE@ICSE, 2013)

A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback. - Robert Tyler Loftin; James MacGlashan; Bei Peng 001; Matthew E. Taylor; Michael L. Littman; Jeff Huang 002; David L. Roberts 001 (AAAI, 2014)

Learning something from nothing: Leveraging implicit human feedback strategies. - Robert Tyler Loftin; Bei Peng 001; James MacGlashan; Michael L. Littman; Matthew E. Taylor; Jeff Huang 002; David L. Roberts 001 (RO-MAN, 2014)

Toward Cyber-Enhanced Working Dogs for Search and Rescue. - Alper Bozkurt; David L. Roberts 001; Barbara L. Sherman; Rita Brugarolas; Sean Mealin; John Majikes; Pu Yang; Robert Tyler Loftin (IEEE Intell. Syst., 2014)

Towards Behavior-Aware Model Learning from Human-Generated Trajectories. - Robert Tyler Loftin; James MacGlashan; Bei Peng 001; Matthew E. Taylor; Michael L. Littman; David L. Roberts 001 (AAAI Fall Symposia, 2016)

A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans. - Bei Peng 001; James MacGlashan; Robert Tyler Loftin; Michael L. Littman; David L. Roberts 001; Matthew E. Taylor (AAMAS, 2016)

Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. - Robert T. Loftin; Bei Peng 001; James MacGlashan; Michael L. Littman; Matthew E. Taylor; Jeff Huang 002; David L. Roberts 001 (Auton. Agents Multi Agent Syst., 2016)

Interactive Learning from Policy-Dependent Human Feedback. - James MacGlashan; Mark K. Ho; Robert Tyler Loftin; Bei Peng 001; Guan Wang; David L. Roberts 001; Matthew E. Taylor; Michael L. Littman (ICML, 2017)

Interactive Learning from Policy-Dependent Human Feedback. - James MacGlashan; Mark K. Ho; Robert Tyler Loftin; Bei Peng 001; David L. Roberts 001; Matthew E. Taylor; Michael L. Littman (CoRR, 2017)

Curriculum Design for Machine Learners in Sequential Decision Tasks. - Bei Peng 001; James MacGlashan; Robert Tyler Loftin; Michael L. Littman; David L. Roberts 001; Matthew E. Taylor (IEEE Trans. Emerg. Top. Comput. Intell., 2018)

Better Exploration with Optimistic Actor Critic. - Kamil Ciosek; Quan Vuong; Robert Tyler Loftin; Katja Hofmann (NeurIPS, 2019)

Interactive Learning of Environment Dynamics for Sequential Tasks. - Robert T. Loftin; Bei Peng 001; Matthew E. Taylor; Michael L. Littman; David L. Roberts 001 (CoRR, 2019)

Strategically efficient exploration in competitive multi-agent reinforcement learning. - Robert Tyler Loftin; Aadirupa Saha; Sam Devlin; Katja Hofmann (UAI, 2021)

On the Impossibility of Learning to Cooperate with Adaptive Partner Strategies in Repeated Games. - Robert Tyler Loftin; Frans A. Oliehoek (ICML, 2022)

Novelty Seeking Multiagent Evolutionary Reinforcement Learning. - Ayhan Alp Aydeniz; Robert Tyler Loftin; Kagan Tumer (GECCO, 2023)

Entropy Maximization in High Dimensional Multiagent State Spaces. - Ayhan Alp Aydeniz; Enrico Marchesini; Robert Tyler Loftin; Kagan Tumer (MRS, 2023)

Towards a Unifying Model of Rationality in Multiagent Systems. - Robert Tyler Loftin; Mustafa Mert Çelikok; Frans A. Oliehoek (CoRR, 2023)

Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. - Robert T. Loftin; Mustafa Mert Çelikok; Herke van Hoof; Samuel Kaski; Frans A. Oliehoek (AAMAS, 2024)

On the Complexity of Learning to Cooperate with Populations of Socially Rational Agents. - Robert Tyler Loftin; Saptarashmi Bandyopadhyay; Mustafa Mert Çelikok (CoRR, 2024)

Safe Multiagent Coordination via Entropic Exploration. - Ayhan Alp Aydeniz; Enrico Marchesini; Robert Tyler Loftin; Christopher Amato; Kagan Tumer (CoRR, 2024)