A Laplacian Framework for Option Discovery in Reinforcement Learning

2 March 2017

Papers citing "A Laplacian Framework for Option Discovery in Reinforcement Learning"

50 / 57 papers shown

Title
NBDI: A Simple and Effective Termination Condition for Skill Extraction from Task-Agnostic Demonstrations Myunsoo Kim Hayeong Lee Seong-Woong Shim JunHo Seo Byung-Jun Lee LLMAG 44 0 0 22 Jan 2025
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations Amirhossein Mesbah Reshad Hosseini Seyed Pooya Shariatpanahi M. N. Ahmadabadi 79 0 0 21 Dec 2024
Synthesizing Evolving Symbolic Representations for Autonomous Systems Gabriele Sartor A. Oddi R. Rasconi V. Santucci Rosa Meo 26 0 0 18 Sep 2024
Efficient Exploration and Discriminative World Model Learning with an Object-Centric Abstraction Anthony GX-Chen Kenneth Marino Rob Fergus OCL 63 1 0 21 Aug 2024
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions Zhening Li Gabriel Poesia Armando Solar-Lezama OffRL 42 1 0 12 Jun 2024
Effective Reinforcement Learning Based on Structural Information Principles Xianghua Zeng Hao Peng Dingli Su Angsheng Li 45 0 0 15 Apr 2024
Memory, Space, and Planning: Multiscale Predictive Representations Ida Momennejad 40 2 0 16 Jan 2024
Proper Laplacian Representation Learning Diego Gomez Michael Bowling Marlos C. Machado 31 1 0 16 Oct 2023
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction Seohong Park Oleh Rybkin Sergey Levine OffRL 38 34 0 13 Oct 2023
Dyadic Reinforcement Learning Shuangning Li L. Niell S. Choi Inbal Nahum-Shani Guy Shani Susan Murphy OffRL 28 2 0 15 Aug 2023
Learning Environment Models with Continuous Stochastic Dynamics Martin Tappler Edi Muškardin B. Aichernig Bettina Könighofer AI4CE 38 1 0 29 Jun 2023
A Cover Time Study of a non-Markovian Algorithm Guanhua Fang G. Samorodnitsky Zhiqiang Xu 28 0 0 08 Jun 2023
Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition Yash Chandak S. Thakoor Z. Guo Yunhao Tang Rémi Munos Will Dabney Diana Borsa 35 2 0 01 May 2023
A Review of Symbolic, Subsymbolic and Hybrid Methods for Sequential Decision Making Carlos Núnez-Molina Pablo Mesejo Juan Fernández-Olivares 39 3 0 20 Apr 2023
Fast exploration and learning of latent graphs with aliased observations Miguel Lazaro-Gredilla Ishani Deshpande Siva K. Swaminathan Meet Dave Dileep George 33 3 0 13 Mar 2023
Predictable MDP Abstraction for Unsupervised Model-Based RL Seohong Park Sergey Levine 29 9 0 08 Feb 2023
Deep Laplacian-based Options for Temporally-Extended Exploration Martin Klissarov Marlos C. Machado OffRL 26 20 0 26 Jan 2023
On the Geometry of Reinforcement Learning in Continuous State and Action Spaces Saket Tiwari Omer Gottesman George Konidaris 29 0 0 29 Dec 2022
Reachability-Aware Laplacian Representation in Reinforcement Learning Kaixin Wang Kuangqi Zhou Jiashi Feng Bryan Hooi Xinchao Wang 36 3 0 24 Oct 2022
Does Zero-Shot Reinforcement Learning Exist? Ahmed Touati Jérémy Rapin Yann Ollivier OffRL 42 39 0 29 Sep 2022
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey A. Aubret L. Matignon S. Hassas 45 35 0 19 Sep 2022
MO2: Model-Based Offline Options Sasha Salter Markus Wulfmeier Dhruva Tirumala N. Heess Martin Riedmiller R. Hadsell Dushyant Rao OffRL 32 13 0 05 Sep 2022
Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren Tianjun Zhang Lisa Lee Joseph E. Gonzalez Dale Schuurmans Bo Dai OffRL 42 27 0 19 Aug 2022
Learning Dynamics and Generalization in Reinforcement Learning Clare Lyle Mark Rowland Will Dabney Marta Z. Kwiatkowska Y. Gal OOD OffRL 35 12 0 05 Jun 2022
Exploration in Deep Reinforcement Learning: A Survey Pawel Ladosz Lilian Weng Minwoo Kim H. Oh OffRL 31 326 0 02 May 2022
Safer Autonomous Driving in a Stochastic, Partially-Observable Environment by Hierarchical Contingency Planning Ugo Lecerf Christelle Yemdji Tchassi Pietro Michiardi 30 1 0 13 Apr 2022
Automatically Learning Fallback Strategies with Model-Free Reinforcement Learning in Safety-Critical Driving Scenarios Ugo Lecerf Christelle Yemdji Tchassi S. Aubert Pietro Michiardi 26 0 0 11 Apr 2022
Unsupervised Learning of Temporal Abstractions with Slot-based Transformers Anand Gopalakrishnan Kazuki Irie Jürgen Schmidhuber Sjoerd van Steenkiste OffRL 28 16 0 25 Mar 2022
Possibility Before Utility: Learning And Using Hierarchical Affordances Robby Costales Shariq Iqbal Fei Sha 34 5 0 23 Mar 2022
A Survey on Recent Advances and Challenges in Reinforcement Learning Methods for Task-Oriented Dialogue Policy Learning Wai-Chung Kwan Hongru Wang Huimin Wang Kam-Fai Wong OffRL 40 43 0 28 Feb 2022
Flexible Option Learning Martin Klissarov Doina Precup OffRL 41 26 0 06 Dec 2021
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching Pierre-Alexandre Kamienny Jean Tarbouriech Sylvain Lamprier A. Lazaric Ludovic Denoyer SSL 45 18 0 27 Oct 2021
Hierarchical Skills for Efficient Exploration Jonas Gehring Gabriel Synnaeve Andreas Krause Nicolas Usunier 28 40 0 20 Oct 2021
Provable Hierarchy-Based Meta-Reinforcement Learning Kurtland Chua Qi Lei Jason D. Lee 22 5 0 18 Oct 2021
DROP: Deep relocating option policy for optimal ride-hailing vehicle repositioning Xinwu Qian Shuocheng Guo Vaneet Aggarwal 23 20 0 09 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 37 80 0 01 Sep 2021
Hierarchical Representation Learning for Markov Decision Processes Lorenzo Steccanella Simone Totaro Anders Jonsson 28 4 0 03 Jun 2021
Discovery of Options via Meta-Learned Subgoals Vivek Veeriah Tom Zahavy Matteo Hessel Zhongwen Xu Junhyuk Oh Iurii Kemaev H. V. Hasselt David Silver Satinder Singh 29 33 0 12 Feb 2021
LISPR: An Options Framework for Policy Reuse with Reinforcement Learning D. Graves Jun Jin Jun Luo 38 2 0 29 Dec 2020
Temporally-Extended ε-Greedy Exploration Will Dabney Georg Ostrovski André Barreto 22 34 0 02 Jun 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee Benjamin Eysenbach Ruslan Salakhutdinov S. Gu Chelsea Finn SSL 24 26 0 06 Apr 2020
Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning? Ofir Nachum Haoran Tang Xingyu Lu S. Gu Honglak Lee Sergey Levine 29 100 0 23 Sep 2019
A Sufficient Statistic for Influence in Structured Multiagent Environments F. Oliehoek Stefan J. Witwicki L. Kaelbling 23 23 0 22 Jul 2019
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives Anirudh Goyal Shagun Sodhani Jonathan Binas Xue Bin Peng Sergey Levine Yoshua Bengio 24 47 0 25 Jun 2019
DAC: The Double Actor-Critic Architecture for Learning Options Shangtong Zhang Shimon Whiteson 30 72 0 29 Apr 2019
Discovering Options for Exploration by Minimizing Cover Time Yuu Jinnai Jee Won Park David Abel George Konidaris 30 52 0 02 Mar 2019
A Meta-MDP Approach to Exploration for Lifelong Reinforcement Learning Francisco M. Garcia Philip S. Thomas 24 38 0 03 Feb 2019
Natural Option Critic Saket Tiwari Philip S. Thomas 22 22 0 04 Dec 2018
Hyperbolic Embeddings for Learning Options in Hierarchical Reinforcement Learning Saket Tiwari M. Prannoy 19 2 0 04 Dec 2018
Unsupervised Control Through Non-Parametric Discriminative Rewards David Warde-Farley T. Wiele Tejas D. Kulkarni Catalin Ionescu Steven Hansen Volodymyr Mnih DRL OffRL SSL 43 173 0 28 Nov 2018