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The ability to continuously acquire new knowledge and skills is crucial for autonomous agents.
Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning
Tianhe Yu, Deirdre Quillen, Zhanpeng He, Ryan Julian, Karol Hausman, Chelsea Finn, and Sergey Levine · 1910
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Catastrophic forgetting, rehearsal and pseudorehearsal
Anthony V. Robins · 1995
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Online fast adaptation and knowledge accumulation: a new approach to continual learning
Massimo Caccia, Pau Rodríguez López, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexande Lacoste, David Vázquez, and Laurent Charlin · 2003
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A fast learning algorithm for deep belief nets
Geoffrey E. Hinton, Simon Osindero, and Yee Whye Teh · 2006
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Scaling learning algorithms towards AI
Yoshua Bengio and Yann LeCun · 2007
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Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
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Powerplay: Training an increasingly general problem solver by continually searching for the simplest still unsolvable problem
Jürgen Schmidhuber · 2013
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Lifelong machine learning systems: Beyond learning algorithms
Daniel L. Silver, Qiang Yang, and Lianghao Li · 2013
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E. Hinton · 2016
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Toward good abstractions for lifelong learning
David Abel, Dilip Arumugam, Lucas Lehnert, and Michael L. Littman · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A. Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, and Raia Hadsell · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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A deep hierarchical approach to lifelong learning in minecraft
Chen Tessler, Shahar Givony, Tom Zahavy, Daniel Mankowitz, and Shie Mannor · 2017
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Essentially no barriers in neural network energy landscape
Felix Draxler, Kambis Veschgini, Manfred Salmhofer, and Fred Hamprecht · 2018
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Loss surfaces, mode connectivity, and fast ensembling of dnns
T. Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P. Vetrov, and Andrew Gordon Wilson · 2018
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Selective experience replay for lifelong learning
David Isele and Akansel Cosgun · 2018
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 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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Unicorn: Continual learning with a universal, off-policy agent
Daniel Jaymin Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, H. V. Hasselt, David Silver, and Tom Schaul · 2018
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Deep online learning via meta-learning: Continual adaptation for model-based rl
Anusha Nagabandi, Chelsea Finn, and Sergey Levine · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech M. Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
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Pseudo-rehearsal: Achieving deep reinforcement learning without catastrophic forgetting
Craig Atkinson, B. McCane, Lech Szymanski, and Anthony V. Robins · 2021
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Loss surface simplexes for mode connecting volumes and fast ensembling
Gregory W. Benton, Wesley Maddox, Sanae Lotfi, and Andrew Gordon Wilson · 2021
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Comps: Continual meta policy search
Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, and Sergey Levine · 2021
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Salina: Sequential learning of agents
Ludovic Denoyer, Alfredo de la Fuente, Song Duong, Jean-Baptiste Gaya, Pierre-Alexandre Kamienny, and Daniel H. Thompson · 2021
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Brax–a differentiable physics engine for large scale rigid body simulation
C Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, and Olivier Bachem · 2021
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Brian Cheung, Alex Terekhov, Yubei Chen, Pulkit Agrawal, and Bruno A. Olshausen · 2019
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Meta-learning representations for continual learning
Khurram Javed and Martha White · 2019
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Policy consolidation for continual reinforcement learning
Christos Kaplanis, Murray Shanahan, and Claudia Clopath · 2019
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Continual lifelong learning with neural networks: A review
German Ignacio Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan, and Stefan Wermter · 2019
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Continual and multi-task architecture search
Ramakanth Pasunuru and Mohit Bansal · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, and Greg Wayne · 2019
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Meta-learnt priors slow down catastrophic forgetting in neural networks
Giacomo Spigler · 2019
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Discorl: Continual reinforcement learning via policy distillation
Kalifou René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Guanghang Cai, Natalia Díaz Rodríguez, and David Filliat · 2019
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Learning a subspace of policies for online adaptation in reinforcement learning
Jean-Baptiste Gaya, Laure Soulier, and Ludovic Denoyer · 2021
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Reset-free lifelong learning with skill-space planning
Kevin Lu, Aditya Grover, P. Abbeel, and Igor Mordatch · 2021
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Linear mode connectivity in multitask and continual learning
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, and Hassan Ghasemzadeh · 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 Kumar Gupta · 2021
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Powerpropagation: A sparsity inducing weight reparameterisation
Jonathan Schwarz, Siddhant Jayakumar, Razvan Pascanu, Peter E Latham, and Yee Teh · 2021
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Block contextual mdps for continual learning
Shagun Sodhani, Franziska Meier, Joelle Pineau, and Amy Zhang · 2021
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Learning neural network subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, and Mohammad Rastegari · 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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Online meta-critic learning for off-policy actor-critic methods
Wei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, and Timothy M. Hospedales · 2021
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CoMPS: Continual meta policy search
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Efficient continual learning ensembles in neural network subspaces
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Same state, different task: Continual reinforcement learning without interference
Samuel Kessler, Jack Parker-Holder, Philip Ball, Stefan Zohren, and Stephen J Roberts · 2022
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Reinforcement learning in presence of discrete markovian context evolution
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