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https://github.com/schatty/awesome-memory-rl
A curated list of awesome memory in reinforcement learning research materials
https://github.com/schatty/awesome-memory-rl
List: awesome-memory-rl
awesome-list deep-learning memory memory-deep-learning memory-mechanisms memory-reinfocement-learning memory-rl reinforcement-learning
Last synced: 3 months ago
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A curated list of awesome memory in reinforcement learning research materials
- Host: GitHub
- URL: https://github.com/schatty/awesome-memory-rl
- Owner: schatty
- License: mit
- Created: 2021-09-05T18:33:22.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-09-05T18:33:39.000Z (about 3 years ago)
- Last Synced: 2024-08-07T22:08:30.114Z (3 months ago)
- Topics: awesome-list, deep-learning, memory, memory-deep-learning, memory-mechanisms, memory-reinfocement-learning, memory-rl, reinforcement-learning
- Homepage:
- Size: 6.84 KB
- Stars: 18
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- ultimate-awesome - awesome-memory-rl - A curated list of awesome memory in reinforcement learning research materials. (Other Lists / PowerShell Lists)
README
# Awesome Memory in RL
[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome#readme)
A curated list of conference papers studying memory mechanisms for reinforcement learning. Also check [awesome-offline-rl](https://github.com/hanjuku-kaso/awesome-offline-rl), [awesome-ebm](https://github.com/yataobian/awesome-ebm), [awesome-model-mbrl](https://github.com/hejia-zhang/awesome-model-based-reinforcement-learning). Forks and PRs are welcome.
## Reinforcement Learning
### 2021
* [End-to-End Egospheric Spatial Memory](https://arxiv.org/abs/2102.07764)
* Daniel Lenton, Stephen James, Ronald Clark, Andrew J. Davison [ICLR]
* [Learning Associative Inference Using Fast Weight Memory](https://arxiv.org/abs/2011.07831)
* Imanol Schlag, Tsendsuren Munkhdalai, Jürgen Schmidhuber [ICLR]
* [Solving Continuous Control with Episodic Memory](https://arxiv.org/abs/2106.08832)
* Igor Kuznetsov, Andrey Filchenkov [IJCAI]
* [Generalizable Episodic Memory for Deep Reinforcement Learning](https://arxiv.org/abs/2103.06469)
* Hao Hu, Jianing Ye, Guangxiang Zhu, Zhizhou Ren, Chongjie Zhang [ICML]
### 2020
* [Episodic Reinforcement Learning with Associative Memory](https://openreview.net/forum?id=HkxjqxBYDB)
* Guangxiang Zhu, Zichuan Lin, Guangwen Yang, Chongjie Zhang [ICLR]
* [AMRL: Aggregated Memory For Reinforcement Learning](https://openreview.net/forum?id=Bkl7bREtDr)
* Jacob Beck, Kamil Ciosek, Sam Devlin, Sebastian Tschiatschek, Cheng Zhang, Katja Hofmann [ICLR]
* [Sparse Graphical Memory for Robust Planning](https://arxiv.org/abs/2003.06417)
* Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak [NeurIPS]
* [Memory Based Trajectory-conditioned Policies for Learning from Sparse Rewards](https://arxiv.org/abs/1907.10247)
* Yijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi, Honglak Lee [NeurIPS]
* [Working Memory Graphs](https://arxiv.org/abs/1911.07141)
* Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht [ICML]
* [Hallucinative Topological Memory for Zero-Shot Visual Planning](https://arxiv.org/abs/2002.12336)
* Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar [ICML]
### 2019
* [Episodic Curiosity through Reachability](https://arxiv.org/abs/1810.02274)
* Nikolay Savinov, Anton Raichuk, Raphaël Marinier, Damien Vincent, Marc Pollefeys, Timothy Lillicrap, Sylvain Gelly [ICLR]
* [Generalization of Reinforcement Learners with Working and Episodic Memory](https://arxiv.org/abs/1910.13406)
* Meire Fortunato, Melissa Tan, Ryan Faulknel et. al [NeurIPS]
* [Policy Consolidation for Continual Reinforcement Learning](https://arxiv.org/abs/1902.00255)
* Christos Kaplanis, Murray Shanahan, Claudia Clopath [ICML]
* [Remember and Forget for Experience Replay](https://arxiv.org/abs/1807.05827)
* Guido Novati, Petros Koumoutsakos [ICML]
* [Reinforcement Learning, Fast and Slow](https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(19)30061-0)
* Matthew Botvinick, Sam Ritter, Jane X. Wang, Zeb Kurth-Nelson, Charles Blundell et. al [Trends in Cognitive Sciences]### 2018
* [Memory Augmented Control Networks](https://arxiv.org/abs/1709.05706)
* Arbaaz Khan, Clark Zhang, Nikolay Atanasov, Konstantinos Karydis, Vijay Kumar, Daniel D. Lee [ICLR]
* [Neural Map: Structured Memory for Deep Reinforcement Learning](https://arxiv.org/abs/1702.08360)
* Emilio Parisotto, Ruslan Salakhutdinov [ICLR]
* [Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing](https://arxiv.org/abs/1807.02322)
* Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc Le, Ni Lao [NeurIPS]
* [Fast deep reinforcement learning using online adjustments from the past](https://arxiv.org/abs/1810.08163)
* Steven Hansen, Pablo Sprechmann, Alexander Pritzel, André Barreto, Charles Blundell [NeurIPS]
* [Continual Reinforcement Learning with Complex Synapses](https://arxiv.org/abs/1802.07239)
* Christos Kaplanis, Murray Shanahan, Claudia Clopath [ICML]
* [Been There, Done That: Meta-Learning with Episodic Recall](https://arxiv.org/abs/1805.09692)
* Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson, Siddhant M. Jayakumar, Charles Blundell et. al [ICML]
* [Episodic Memory Deep Q-Networks](https://arxiv.org/abs/1805.07603)
* Zichuan Lin, Tianqi Zhao, Guangwen Yang, Lintao Zhang [IJCAI]
* [Unsupervised Predictive Memory in a Goal-Directed Agent ](https://arxiv.org/abs/1803.10760)
* Greg Wayne, Chia-Chun Hung, David Amos et. al### 2017
* [Fast Reinforcement Learning via Slow Reinforcement Learning](https://arxiv.org/abs/1611.02779)
* Yan Duan, John Schulman, Xi Chen, Peter L. Bartlett, Ilya Sutskever, Pieter Abbeel [ICLR]
* [Neural Episodic Control](https://arxiv.org/abs/1703.01988)
* Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech, Oriol Vinyals, Demis Hassabil et. al [ICML]### ... - 2016
* [Using Fast Weights to Attend to the Recent Past](https://arxiv.org/abs/1610.06258)
* Jimmy Ba, Geoffrey Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu [NIPS-2016]
* [Control of Memory, Active Perception, and Action in Minecraft](https://arxiv.org/abs/1605.09128)
* Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee [ICLR-2016]
* [Model-Free Episodic Control](https://arxiv.org/abs/1606.04460)
* Charles Blundell, Benigno Uria, Alexander Pritzel et. al
* [Hippocampal Contributions to Control: The Third Way](https://proceedings.neurips.cc/paper/2007/hash/1f4477bad7af3616c1f933a02bfabe4e-Abstract.html)
* Máté Lengyel, Peter Dayan [NIPS-2007]## Deep Learning
### 2021
* [Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting](https://arxiv.org/abs/2010.01528)
* Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell [ICLR]
* [Gradient Projection Memory for Continual Learning](https://arxiv.org/abs/2103.09762)
* Gobinda Saha, Isha Garg, Kaushik Roy [ICLR]
* [Learn from Concepts: Towards the Purified Memory for Few-shot Learning](https://www.ijcai.org/proceedings/2021/123)
* Xuncheng Liu, Xudong Tian, Shaohui Lin, Yanyun Qu, Lizhuang Ma, Wang Yuan, Zhizhong Zhang, Yuan Xi [IJCAI]
* [Not All Memories are Created Equal: Learning to Forget by Expiring](https://arxiv.org/abs/2105.06548)
* Sainbayar Sukhbaatar, Da Ju, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan [ICML]### 2020
* [Memory-Based Graph Networks](https://arxiv.org/abs/2002.09518)
* Amir Hosein Khasahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris [ICLR]
* [Meta-Learning Deep Energy-Based Memory Models](https://arxiv.org/abs/1910.02720)
* Sergey Bartunov, Jack W Rae, Simon Osindero, Timothy P Lillicrap [ICLR]
* [MEMO: A Deep Network for Flexible Combination of Episodic Memories](https://arxiv.org/abs/2001.10913)
* Andrea Banino, Adrià Puigdomènech Badia, Raphael Köster et. al [ICLR]
* [Progressive Memory Banks for Incremental Domain Adaptation](https://arxiv.org/abs/1811.00239)
* Nabiha Asghar, Lili Mou, Kira A. Selby, Kevin D. Pantasdo, Pascal Poupart, Xin Jiang [ICLR]
* [Neural Stored-program Memory](https://arxiv.org/abs/1906.08862)
* Hung Le, Truyen Tran, Svetha Venkatesh [ICLR]
* [H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks](https://proceedings.neurips.cc/paper/2020/file/f6876a9f998f6472cc26708e27444456-Paper.pdf)
* Thomas Limbacher and Robert Legenstein [NeurIPS]
* [Online Multitask Learning with Long-Term Memory](https://arxiv.org/abs/2008.07055)
* Mark Herbster, Stephen Pasteris, Lisa Tse [NeurIPS]
* [HiPPO: Recurrent Memory with Optimal Polynomial Projections](https://arxiv.org/abs/2008.07669)
* Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Re [NeurIPS]
* [Learning to Learn Variational Semantic Memory](https://arxiv.org/abs/2010.10341)
* Xiantong Zhen, Yingjun Du, Huan Xiong, Qiang Qiu, Cees G. M. Snoek, Ling Shao [NeurIPS]
* [Improved Schemes for Episodic Memory-based Lifelong Learning](https://arxiv.org/abs/1909.11763)
* Yunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing [NeurIPS]
* [Self-Attentive Associative Memory](https://arxiv.org/abs/2002.03519)
* Hung Le, Truyen Tran, Svetha Venkatesh [ICML]
* [Associative Memory in Iterated Overparameterized Sigmoid Autoencoders](https://arxiv.org/abs/2006.16540)
* Yibo Jiang, Cengiz Pehlevan [ICML]
* [Multigrid Neural Memory](https://arxiv.org/abs/1906.05948)
* Tri Huynh, Michael Maire, Matthew R. Walter [ICML]### 2019
* [Learning to Remember More with Less Memorization](https://arxiv.org/abs/1901.01347)
* Hung Le, Truyen Tran, Svetha Venkatesh [ICLR]
* [Adaptive Posterior Learning: few-shot learning with a surprise-based memory module](https://arxiv.org/abs/1902.02527)
* Tiago Ramalho, Marta Garnelo [ICLR]
* [Large Memory Layers with Product Keys](https://arxiv.org/abs/1907.05242)
* Guillaume Lample, Alexandre Sablayrolles, Marc'Aurelio Ranzato, Ludovic Denoyer, Hervé Jégou [NeurIPS]
* [Episodic Memory in Lifelong Language Learning](https://arxiv.org/abs/1906.01076)
* Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, Dani Yogatama [NeurIPS]
* [Metalearned Neural Memory](https://arxiv.org/abs/1907.09720)
* Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler [NeurIPS]
* [Ordered Memory](https://arxiv.org/abs/1910.13466)
* Yikang Shen, Shawn Tan, Arian Hosseini, Zhouhan Lin, Alessandro Sordoni, Aaron Courville [NeurIPS]
* [Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks](https://papers.nips.cc/paper/2019/file/952285b9b7e7a1be5aa7849f32ffff05-Paper.pdf)
* Aaron R. Voelker, Ivana Kajic ́, Chris Eliasmith [NeurIPS]### 2018
* [Semi-parametric Topological Memory for Navigation](https://arxiv.org/abs/1803.00653)
* Nikolay Savinov, Alexey Dosovitskiy, Vladlen Koltun [ICLR]
* [Memory-based Parameter Adaptation](https://arxiv.org/abs/1802.10542)
* Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae, Alexander Pritzel et. al [ICLR]
* [Convolutional Memory Blocks for Depth Data Representation Learning](https://www.ijcai.org/proceedings/2018/0387.pdf)
* Keze Wang, Liang Lin, Chuangjie Ren, Wei Zhang, Wenxiu Sun [IJCAI]
* [Visual Memory for Robust Path Following](https://arxiv.org/abs/1812.00940)
* Ashish Kumar, Saurabh Gupta, David Fouhey, Sergey Levine, Jitendra Malik [NeurIPS]
* [A Simple Cache Model for Image Recognition](https://arxiv.org/abs/1805.08709)
* A. Emin Orhan [NeurIPS]
* [Variational Memory Encoder-Decoder](https://arxiv.org/abs/1807.09950)
* Hung Le, Truyen Tran, Thin Nguyen, Svetha Venkatesh [NeurIPS]
* [Fast Parametric Learning with Activation Memorization](https://arxiv.org/abs/1803.10049)
* Jack W Rae, Chris Dyer, Peter Dayan, Timothy P Lillicrap [ICML]
* [Learning and Memorization](http://proceedings.mlr.press/v80/chatterjee18a.html)
* Satrajit Chatterjee [ICML]### 2017
* [Reasoning with Memory Augmented Neural Networks for Language Comprehension](https://arxiv.org/abs/1610.06454)
* Tsendsuren Munkhdalai, Hong Yu [ICLR]
* [Learning to Remember Rare Events](https://arxiv.org/abs/1703.03129)
* Łukasz Kaiser, Ofir Nachum, Aurko Roy, Samy Bengio [ICLR]
* [Variational Memory Addressing in Generative Models](https://arxiv.org/abs/1709.07116)
* Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo J. Rezende [NIPS]
* [A simple model of recognition and recall memory](https://papers.nips.cc/paper/2017/hash/57aeee35c98205091e18d1140e9f38cf-Abstract.html)
* Nisheeth Srivastava, Edward Vul [NIPS]
* [Gradient Episodic Memory for Continual Learning](https://arxiv.org/abs/1706.08840)
* David Lopez-Paz, Marc'Aurelio Ranzato [NIPS]### ... - 2016
* [End-To-End Memory Networks](https://arxiv.org/abs/1503.08895) [NIPS-205]
## Cognition and Neuroscience
* [Large Associative Memory Problem in Neurobiology and Machine Learning](https://arxiv.org/abs/2008.06996)
* Dmitry Krotov, John Hopfield [ICLR-2021]
* [Compositional Explanations of Neurons](https://arxiv.org/abs/2006.14032)
* Jesse Mu, Jacob Andreas [NeurIPS-2020]
* [Coordinated hippocampal-entorhinal replay as structural inference](https://proceedings.neurips.cc/paper/2019/hash/aa68c75c4a77c87f97fb686b2f068676-Abstract.html)
* Talfan Evans, Neil Burgess [NeurIPS-2019]
* [Generalisation of structural knowledge in the hippocampal-entorhinal system](https://arxiv.org/abs/1805.09042)
* James C. R. Whittington, Timothy H. Muller, Shirley Mark, Caswell Barry, Timothy E. J. Behrens [NeurIPS-2018]
* [Dendritic cortical microcircuits approximate the backpropagation algorithm](https://arxiv.org/abs/1810.11393)
* João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn [NeurIPS-2018]