Lifelong Inverse Reinforcement Learning. - Jorge A. Mendez; Shashank Shivkumar; Eric Eaton (NeurIPS, 2018)

Transfer Learning via Minimizing the Performance Gap Between Domains. - Boyu Wang; Jorge A. Mendez; Mingbo Cai; Eric Eaton (NeurIPS, 2019)

Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting. - Jorge A. Mendez; Boyu Wang; Eric Eaton (NeurIPS, 2020)

Lifelong Learning of Compositional Structures. - Jorge A. Mendez; Eric Eaton (ICLR, 2021)

SHELS: Exclusive Feature Sets for Novelty Detection and Continual Learning Without Class Boundaries. - Meghna Gummadi; David Kent 001; Jorge A. Mendez; Eric Eaton (CoLLAs, 2022)

CompoSuite: A Compositional Reinforcement Learning Benchmark. - Jorge A. Mendez; Marcel Hussing; Meghna Gummadi; Eric Eaton (CoLLAs, 2022)

Modular Lifelong Reinforcement Learning via Neural Composition. - Jorge A. Mendez; Harm van Seijen; Eric Eaton (ICLR, 2022)

Gap Minimization for Knowledge Sharing and Transfer. - Boyu Wang 004; Jorge A. Mendez; Changjian Shui; Fan Zhou 006; Di Wu 044; Christian Gagné 001; Eric Eaton (CoRR, 2022)

Reinforcement Learning of Multi-Domain Dialog Policies Via Action Embeddings. - Jorge A. Mendez; Alborz Geramifard; Mohammad Ghavamzadeh; Bing Liu (CoRR, 2022)

Lifelong Machine Learning of Functionally Compositional Structures. - Jorge A. Mendez (CoRR, 2022)

Embodied Lifelong Learning for Task and Motion Planning. - Jorge A. Mendez; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRR, 2023)

Gap Minimization for Knowledge Sharing and Transfer. - Boyu Wang 004; Jorge A. Mendez; Changjian Shui; Fan Zhou 006; Di Wu 044; Gezheng Xu; Christian Gagné 001; Eric Eaton (J. Mach. Learn. Res., 2023)

How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition. - Jorge A. Mendez; Eric Eaton (Trans. Mach. Learn. Res., 2023)

A domain-agnostic approach for characterization of lifelong learning systems. - Megan M. Baker; Alexander New; Mario Aguilar-Simon; Ziad Al-Halah; Sébastien M. R. Arnold; Eseoghene Ben-Iwhiwhu; Andrew P. Brna; Ethan Brooks; Ryan C. Brown; Zachary Daniels; Anurag Reddy Daram; Fabien Delattre; et al. (Neural Networks, 2023)

Robotic Manipulation Datasets for Offline Compositional Reinforcement Learning. - Marcel Hussing; Jorge A. Mendez; Anisha Singrodia; Cassandra Kent; Eric Eaton (RLJ, 2024)