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Lifelong learning offers a promising paradigm of building a generalist agent that learns and adapts over its lifespan.
Mixture density networks
Christopher M Bishop · 1994
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A framework for behavioural cloning
Michael Bain and Claude Sammut · 1995
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Lifelong robot learning
Sebastian Thrun and Tom M Mitchell · 1995
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Multitask learning
Rich Caruana · 1997
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Pddl-the planning domain definition language
Drew McDermott, Malik Ghallab, Adele Howe, Craig Knoblock, Ashwin Ram, Manuela Veloso, Daniel Weld, and David Wilkins · 1998
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
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The mnist database of handwritten digit images for machine learning research
Li Deng · 2012
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Deep recurrent q-learning for partially observable mdps
Matthew Hausknecht and Peter Stone · 2015
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Vizdoom: A doom-based ai research platform for visual reinforcement learning
Michał Kempka, Marek Wydmuch, Grzegorz Runc, Jakub Toczek, and Wojciech Jaśkowski · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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Visualizing and understanding atari agents
Sam Greydanus, Anurag Koul, Jonathan Dodge, and Alan Fern · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Core50: a new dataset and benchmark for continuous object recognition
Vincenzo Lomonaco and Davide Maltoni · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2017
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Don’t forget, there is more than forgetting: new metrics for continual learning
Natalia Díaz-Rodríguez, Vincenzo Lomonaco, David Filliat, and Davide Maltoni · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2018
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On tiny episodic memories in continual learning
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 2019
Cited alongside, same era.
Superposition of many models into one
Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, and Bruno Olshausen · 2019
What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations
Tongzhou Mu, Zhan Ling, Fanbo Xiang, Derek Yang, Xuanlin Li, Stone Tao, Zhiao Huang, Zhiwei Jia, and Hao Su · 2021
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Cora: Benchmarks, baselines, and metrics as a platform for continual reinforcement learning agents
Sam Powers, Eliot Xing, Eric Kolve, Roozbeh Mottaghi, and Abhinav Gupta · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Compacting, picking and growing for unforgetting continual learning
Ching-Yi Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
Cited alongside, same era.
Causalworld: A robotic manipulation benchmark for causal structure and transfer learning
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Yoshua Bengio, Bernhard Schölkopf, Manuel Wüthrich, and Stefan Bauer · 2020
Cited alongside, same era.
Continual lifelong learning in natural language processing: A survey
Magdalena Biesialska, Katarzyna Biesialska, and Marta R Costa-Jussa · 2020
Cited alongside, same era.
Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
Cited alongside, same era.
Leveraging procedural generation to benchmark reinforcement learning
Karl Cobbe, Chris Hesse, Jacob Hilton, and John Schulman · 2020
Cited alongside, same era.
Space: Structured compression and sharing of representational space for continual learning
Gobinda Saha, Isha Garg, Aayush Ankit, and Kaushik Roy · 2021
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Minihack the planet: A sandbox for open-ended reinforcement learning research
Mikayel Samvelyan, Robert Kirk, Vitaly Kurin, Jack Parker-Holder, Minqi Jiang, Eric Hambro, Fabio Petroni, Heinrich Küttler, Edward Grefenstette, and Tim Rocktäschel · 2021
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Open-ended learning leads to generally capable agents
Open Ended Learning Team, Adam Stooke, Anuj Mahajan, Catarina Barros, Charlie Deck, Jakob Bauer, Jakub Sygnowski, Maja Trebacz, Max Jaderberg, Michael Mathieu, et al · 2021
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Continual world: A robotic benchmark for continual reinforcement learning
Maciej Wołczyk, Michal Zajkac, Razvan Pascanu, Lukasz Kuci’nski, and Piotr Milo’s · 2021
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Few-shot continual active learning by a robot
Ali Ayub and Carter Fendley · 2022
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Lifelong reinforcement learning with modulating masks
Eseoghene Ben-Iwhiwhu, Saptarshi Nath, Praveen K Pilly, Soheil Kolouri, and Andrea Soltoggio · 2022
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Memory efficient continual learning with transformers
Beyza Ermis, Giovanni Zappella, Martin Wistuba, and Cédric Archambeau · 2022
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Ego4d: Around the world in 3,000 hours of egocentric video
Kristen Grauman, Andrew Westbury, Eugene Byrne, Zachary Chavis, Antonino Furnari, Rohit Girdhar, Jackson Hamburger, Hao Jiang, Miao Liu, Xingyu Liu, et al · 2022
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Class-incremental learning by knowledge distillation with adaptive feature consolidation
Minsoo Kang, Jaeyoo Park, and Bohyung Han · 2022
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Continual learning and private unlearning
B. Liu, Qian Liu, and Peter Stone · 2022
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Continual learning with recursive gradient optimization
Hao Liu and Huaping Liu · 2022
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Online continual learning in image classification: An empirical survey
Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim, and Scott Sanner · 2022
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Composuite: A compositional reinforcement learning benchmark
Jorge A Mendez, Marcel Hussing, Meghna Gummadi, and Eric Eaton · 2022
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Architecture matters in continual learning
Seyed Iman Mirzadeh, Arslan Chaudhry, Dong Yin, Timothy Nguyen, Razvan Pascanu, Dilan Gorur, and Mehrdad Farajtabar · 2022
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Behavior: Benchmark for everyday household activities in virtual, interactive, and ecological environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach, Roberto Martín-Martín, Fei Xia, Kent Elliott Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, Karen Liu, et al · 2022
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Disentangling transfer in continual reinforcement learning
Maciej Wołczyk, Michal Zajkac, Razvan Pascanu, Lukasz Kuci’nski, and Piotr Milo’s · 2022
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Forward compatible few-shot class-incremental learning
Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, and De-Chuan Zhan · 2022
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Viola: Imitation learning for vision-based manipulation with object proposal priors
Yifeng Zhu, Abhishek Joshi, Peter Stone, and Yuke Zhu · 2022
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Maniskill2: A unified benchmark for generalizable manipulation skills
Jiayuan Gu, Fanbo Xiang, Xuanlin Li, Zhan Ling, Xiqiang Liu, Tongzhou Mu, Yihe Tang, Stone Tao, Xinyue Wei, Yunchao Yao, et al · 2023
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Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation
Chengshu Li, Ruohan Zhang, Josiah Wong, Cem Gokmen, Sanjana Srivastava, Roberto Martín-Martín, Chen Wang, Gabrael Levine, Michael Lingelbach, Jiankai Sun, et al · 2023
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Mimicplay: Long-horizon imitation learning by watching human play
Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, and Anima Anandkumar · 2023
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