Exploration by Random Network Distillation

30 October 2018

Amos Storkey

Papers citing "Exploration by Random Network Distillation"

40 / 290 papers shown

Title
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration Zhenghao Peng Hao Sun Bolei Zhou 18 18 0 14 Jun 2020
Primal Wasserstein Imitation Learning Robert Dadashi Léonard Hussenot M. Geist Olivier Pietquin 26 124 0 08 Jun 2020
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals Henry Charlesworth Giovanni Montana OffRL 29 24 0 01 Jun 2020
Novel Policy Seeking with Constrained Optimization Hao Sun Zhenghao Peng Bo Dai Jian Guo Dahua Lin Bolei Zhou 24 13 0 21 May 2020
Planning to Explore via Self-Supervised World Models Ramanan Sekar Oleh Rybkin Kostas Daniilidis Pieter Abbeel Danijar Hafner Deepak Pathak SSL 33 397 0 12 May 2020
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning Z. Guo Bernardo Avila-Pires Bilal Piot Jean-Bastien Grill Florent Altché Rémi Munos M. G. Azar BDL DRL SSL 43 139 0 30 Apr 2020
First return, then explore Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune 47 350 0 27 Apr 2020
Agent57: Outperforming the Atari Human Benchmark Adria Puigdomenech Badia Bilal Piot Steven Kapturowski Pablo Sprechmann Alex Vitvitskyi Daniel Guo Charles Blundell OffRL 27 509 0 30 Mar 2020
Analyzing Visual Representations in Embodied Navigation Tasks Erik Wijmans Julian Straub Dhruv Batra Irfan Essa Judy Hoffman Ari S. Morcos 17 2 0 12 Mar 2020
Automatic Curriculum Learning For Deep RL: A Short Survey Rémy Portelas Cédric Colas Lilian Weng Katja Hofmann Pierre-Yves Oudeyer ODL 19 167 0 10 Mar 2020
Scaling MAP-Elites to Deep Neuroevolution Cédric Colas Joost Huizinga Vashisht Madhavan Jeff Clune 33 86 0 03 Mar 2020
On the Sensory Commutativity of Action Sequences for Embodied Agents Hugo Caselles-Dupré Michael Garcia Ortiz David Filliat 19 4 0 13 Feb 2020
Bayesian Residual Policy Optimization: Scalable Bayesian Reinforcement Learning with Clairvoyant Experts Gilwoo Lee Brian Hou Sanjiban Choudhury S. Srinivasa BDL OffRL 31 7 0 07 Feb 2020
Population-Guided Parallel Policy Search for Reinforcement Learning Whiyoung Jung Giseung Park Y. Sung OffRL 24 38 0 09 Jan 2020
An Exploration of Embodied Visual Exploration Santhosh Kumar Ramakrishnan Dinesh Jayaraman Kristen Grauman LM&Ro 32 98 0 07 Jan 2020
Dota 2 with Large Scale Deep Reinforcement Learning OpenAI OpenAI : Christopher Berner Greg Brockman Brooke Chan ... Szymon Sidor Ilya Sutskever Jie Tang Filip Wolski Susan Zhang GNN VLM CLL AI4CE LRM 41 1,795 0 13 Dec 2019
Implicit Generative Modeling for Efficient Exploration Neale Ratzlaff Qinxun Bai Fuxin Li Wenyuan Xu 22 12 0 19 Nov 2019
Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning Dipendra Kumar Misra Mikael Henaff A. Krishnamurthy John Langford 21 151 0 13 Nov 2019
Explicit Explore-Exploit Algorithms in Continuous State Spaces Mikael Henaff OffRL 22 31 0 01 Nov 2019
Dealing with Sparse Rewards in Reinforcement Learning J. Hare 21 77 0 21 Oct 2019
Influence-Based Multi-Agent Exploration Tonghan Wang Jianhao Wang Yi Wu Chongjie Zhang 21 137 0 12 Oct 2019
Receding Horizon Curiosity M. Schultheis Boris Belousov Hany Abdulsamad Jan Peters 25 15 0 08 Oct 2019
Benchmarking Batch Deep Reinforcement Learning Algorithms Shih-Han Chou Wen-Yen Chang W. Hsu Jianlong Fu OffRL 15 181 0 03 Oct 2019
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms Oliver Kroemer S. Niekum George Konidaris 36 356 0 06 Jul 2019
Growing Action Spaces Gregory Farquhar Laura Gustafson Zeming Lin Shimon Whiteson Nicolas Usunier Gabriel Synnaeve 14 38 0 28 Jun 2019
Optimistic Proximal Policy Optimization Takahisa Imagawa Takuya Hiraoka Yoshimasa Tsuruoka 15 4 0 25 Jun 2019
Interpretable Few-Shot Learning via Linear Distillation Arip Asadulaev Igor Kuznetsov Andrey Filchenkov FedML FAtt 11 1 0 13 Jun 2019
Design of Artificial Intelligence Agents for Games using Deep Reinforcement Learning A. Roibu 27 1 0 10 May 2019
Teaching on a Budget in Multi-Agent Deep Reinforcement Learning Ercüment Ilhan Jeremy Gow Diego Perez-Liebana 24 35 0 19 Apr 2019
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics Denis Steckelmacher Hélène Plisnier D. Roijers A. Nowé OffRL 23 17 0 11 Mar 2019
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning Vitchyr H. Pong Murtaza Dalal Steven Lin Ashvin Nair Shikhar Bahl Sergey Levine OffRL SSL 33 269 0 08 Mar 2019
Hyperbolic Discounting and Learning over Multiple Horizons W. Fedus Carles Gelada Yoshua Bengio Marc G. Bellemare Hugo Larochelle 32 105 0 19 Feb 2019
Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning Andrew Silva Matthew C. Gombolay OffRL 27 20 0 15 Feb 2019
Go-Explore: a New Approach for Hard-Exploration Problems Adrien Ecoffet Joost Huizinga Joel Lehman Kenneth O. Stanley Jeff Clune AI4TS 24 361 0 30 Jan 2019
Never Forget: Balancing Exploration and Exploitation via Learning Optical Flow Hsuan-Kung Yang Po-Han Chiang Kuan-Wei Ho Min-Fong Hong Chun-Yi Lee 35 7 0 24 Jan 2019
Amplifying the Imitation Effect for Reinforcement Learning of UCAV's Mission Execution G. Lee Chang Ouk Kim 10 4 0 17 Jan 2019
On the potential for open-endedness in neural networks N. Guttenberg N. Virgo A. Penn 21 10 0 12 Dec 2018
Provably Efficient Maximum Entropy Exploration Elad Hazan Sham Kakade Karan Singh A. V. Soest 33 292 0 06 Dec 2018
Episodic Curiosity through Reachability Nikolay Savinov Anton Raichuk Raphaël Marinier Damien Vincent Marc Pollefeys Timothy Lillicrap Sylvain Gelly 14 266 0 04 Oct 2018
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,327 0 05 Nov 2016