Interactive visual clustering. - Marie desJardins; James MacGlashan; Julia Ferraioli (IUI, 2007)

Hierarchical Skill Learning for High-Level Planning. - James MacGlashan (AAAI, 2010)

A Game Playing System for Use in Computer Science Education. - James MacGlashan; Don Miner; Marie desJardins (FLAIRS, 2010)

Confidence-Based Feature Acquisition to Minimize Training and Test Costs. - Marie desJardins; James MacGlashan; Kiri L. Wagstaff (SDM, 2010)

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)

Affordances as Transferable Knowledge for Planning Agents. - Gabriel Barth-Maron; David Abel; James MacGlashan; Stefanie Tellex (AAAI Fall Symposia, 2014)

Discovering Subgoals in Complex Domains. - Marie desJardins; Tenji Tembo; Nicholay Topin; Michael Bishoff; Shawn Squire; James MacGlashan; Rose Carignan; Nicholas Haltmeyer (AAAI Fall Symposia, 2014)

Flexible theft and resolute punishment: Evolutionary dynamics of social behavior among reinforcement-learning agents. - James MacGlashan; Michael L. Littman; Fiery Cushman (CogSci, 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)

Minecraft as an Experimental World for AI in Robotics. - Krishna Chaitanya Aluru; Stefanie Tellex; John Oberlin; James MacGlashan (AAAI Fall Symposia, 2015)

Learning Propositional Functions for Planning and Reinforcement Learning. - David Ellis Hershkowitz; James MacGlashan; Stefanie Tellex (AAAI Fall Symposia, 2015)

Robotic Social Feedback for Object Specification. - Emily Wu; Yuxin Han; David Whitney; John Oberlin; James MacGlashan; Stefanie Tellex (AAAI Fall Symposia, 2015)

Goal-Based Action Priors. - David Abel; D. Ellis Hershkowitz; Gabriel Barth-Maron; Stephen Brawner; Kevin O'Farrell; James MacGlashan; Stefanie Tellex (ICAPS, 2015)

Between Imitation and Intention Learning. - James MacGlashan; Michael L. Littman (IJCAI, 2015)

Portable Option Discovery for Automated Learning Transfer in Object-Oriented Markov Decision Processes. - Nicholay Topin; Nicholas Haltmeyer; Shawn Squire; John Winder; Marie desJardins; James MacGlashan (IJCAI, 2015)

Grounding English Commands to Reward Functions. - James MacGlashan; Monica Babes-Vroman; Marie desJardins; Michael L. Littman; Smaranda Muresan; Shawn Squire; Stefanie Tellex; Dilip Arumugam; Lei Yang 003 (Robotics: Science and Systems, 2015)

Reinforcement Learning as a Framework for Ethical Decision Making. - David Abel; James MacGlashan; Michael L. Littman (AAAI Workshop: AI, Ethics, and Society, 2016)

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)

Feature-based Joint Planning and Norm Learning in Collaborative Games. - Mark K. Ho; James MacGlashan; Amy Greenwald; Michael L. Littman; Elizabeth Hilliard; Carl Trimbach; Stephen Brawner; Josh Tenenbaum 001; Max Kleiman-Weiner; Joseph L. Austerweil (CogSci, 2016)

Showing versus doing: Teaching by demonstration. - Mark K. Ho; Michael L. Littman; James MacGlashan; Fiery Cushman; Joseph L. Austerweil (NIPS, 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)

Planning with Abstract Markov Decision Processes. - Nakul Gopalan; Marie desJardins; Michael L. Littman; James MacGlashan; Shawn Squire; Stefanie Tellex; John Winder; Lawson L. S. Wong (ICAPS, 2017)

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)

Reducing errors in object-fetching interactions through social feedback. - David Whitney; Eric Rosen; James MacGlashan; Lawson L. S. Wong; Stefanie Tellex (ICRA, 2017)

Environment-Independent Task Specifications via GLTL. - Michael L. Littman; Ufuk Topcu; Jie Fu 002; Charles Lee Isbell Jr.; Min Wen; James MacGlashan (CoRR, 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)

Implementing the Deep Q-Network. - Melrose Roderick; James MacGlashan; Stefanie Tellex (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)

Gamma-Nets: Generalizing Value Estimation over Timescale. - Craig Sherstan; Shibhansh Dohare; James MacGlashan; Johannes Günther 002; Patrick M. Pilarski (AAAI, 2020)

Efficient Real-Time Inference in Temporal Convolution Networks. - Piyush Khandelwal; James MacGlashan; Peter R. Wurman; Peter Stone 001 (ICRA, 2021)

Value Function Decomposition for Iterative Design of Reinforcement Learning Agents. - James MacGlashan; Evan Archer; Alisa Devlic; Takuma Seno; Craig Sherstan; Peter R. Wurman; Peter Stone 001 (NeurIPS, 2022)

Outracing champion Gran Turismo drivers with deep reinforcement learning. - Peter R. Wurman; Samuel Barrett; Kenta Kawamoto; James MacGlashan; Kaushik Subramanian; Thomas J. Walsh 001; Roberto Capobianco; Alisa Devlic; Franziska Eckert; Florian Fuchs 004; Leilani Gilpin; Piyush Khandelwal; et al. (Nat., 2022)