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)

A Framework for Anomaly Reasoning: Interpretation through Concept Formation for Knowledge Transfer and Lifelong Learning. - John Winder (IJCAI, 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)

Feature Construction for Controlling Swarms by Visual Demonstration. - Karan K. Budhraja; John Winder; Tim Oates 001 (ACM Trans. Auton. Adapt. Syst., 2017)

Concept-Aware Feature Extraction for Knowledge Transfer in Reinforcement Learning. - John Winder; Marie desJardins (AAAI Workshops, 2018)

The Expected-Length Model of Options. - David Abel; John Winder; Marie desJardins; Michael L. Littman (IJCAI, 2019)

Segmentation of breast MR images using a generalised 2D mathematical model with inflation and deflation forces of active contours. - Andrik Rampun; Bryan W. Scotney; Philip J. Morrow; Hui Wang 001; John Winder (Artif. Intell. Medicine, 2019)

Planning with Abstract Learned Models While Learning Transferable Subtasks. - John Winder; Stephanie Milani; Matthew Landen; Erebus Oh; Shane Parr; Shawn Squire; Marie desJardins; Cynthia Matuszek (AAAI, 2020)

Presentation and Analysis of a Multimodal Dataset for Grounded LanguageLearning. - Patrick Jenkins; Rishabh Sachdeva; Gaoussou Youssouf Kebe; Padraig Higgins; Kasra Darvish; Edward Raff; Don Engel; John Winder; Francis Ferraro; Cynthia Matuszek (CoRR, 2020)

A Spoken Language Dataset of Descriptions for Speech-Based Grounded Language Learning. - Gaoussou Youssouf Kebe; Padraig Higgins; Patrick Jenkins; Kasra Darvish; Rishabh Sachdeva; Ryan Barron; John Winder; Don Engel; Edward Raff; Francis Ferraro; Cynthia Matuszek (NeurIPS Datasets and Benchmarks, 2021)

Adaptive Neural Networks Using Residual Fitting. - Noah Ford; John Winder; Joshua McClellan (CoRR, 2023)

Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance. - Joshua McClellan; Naveed Haghani; John Winder; Furong Huang; Pratap Tokekar (NeurIPS, 2024)

Uncovering Uncertainty in Transformer Inference. - Greyson Brothers; Willa Mannering; Amber Tien; John Winder (CoRR, 2024)