DeepMDP: Learning Continuous Latent Space Models for Representation Learning

6 June 2019

Papers citing "DeepMDP: Learning Continuous Latent Space Models for Representation Learning"

50 / 94 papers shown

Title
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning Samuel Garcin Trevor A. McInroe Pablo Samuel Castro Prakash Panangaden Christopher G. Lucas David Abel Stefano V. Albrecht 58 0 0 08 Mar 2025
Risk-averse policies for natural gas futures trading using distributional reinforcement learning Félicien Hêche Biagio Nigro Oussama Barakat Stephan Robert-Nicoud OffRL 46 0 0 08 Jan 2025
Approximate Equivariance in Reinforcement Learning Jung Yeon Park Sujay Bhatt Sihan Zeng Lawson L. S. Wong Alec Koppel Sumitra Ganesh Robin Walters 45 1 0 06 Nov 2024
Next state prediction gives rise to entangled, yet compositional representations of objects Tankred Saanum Luca M. Schulze Buschoff Peter Dayan Eric Schulz OCL CoGe OOD 42 1 0 07 Oct 2024
Feasibility Consistent Representation Learning for Safe Reinforcement Learning Zhepeng Cen Yi-Fan Yao Zuxin Liu Ding Zhao OffRL 45 3 0 20 May 2024
Model-based Reinforcement Learning for Parameterized Action Spaces Renhao Zhang Haotian Fu Yilin Miao George Konidaris 31 3 0 03 Apr 2024
Closing the Gap between TD Learning and Supervised Learning -- A Generalisation Point of View Raj Ghugare Matthieu Geist Glen Berseth Benjamin Eysenbach OffRL 40 14 0 20 Jan 2024
Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni Benjamin Eysenbach Erfan Seyedsalehi Michel Ma Clement Gehring Aditya Mahajan Pierre-Luc Bacon AI4TS AI4CE 29 21 0 17 Jan 2024
Interventionally Consistent Surrogates for Agent-based Simulators Joel Dyer Nicholas Bishop Yorgos Felekis Fabio Massimo Zennaro Anisoara Calinescu Theodoros Damoulas Michael Wooldridge 21 6 0 18 Dec 2023
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Tongzheng Ren Chenjun Xiao Dale Schuurmans Bo Dai 47 4 0 20 Nov 2023
Novelty Detection in Reinforcement Learning with World Models Geigh Zollicoffer Kenneth Eaton Jonathan C. Balloch Julia Kim Mark O. Riedl Robert Wright Mark O. Riedl 30 1 0 12 Oct 2023
A Kernel Perspective on Behavioural Metrics for Markov Decision Processes Pablo Samuel Castro Tyler Kastner Prakash Panangaden Mark Rowland 46 4 0 05 Oct 2023
RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability Chuning Zhu Max Simchowitz Siri Gadipudi Abhishek Gupta 46 13 0 31 Aug 2023
$λ$ -models: Effective Decision-Aware Reinforcement Learning with Latent Models C. Voelcker Arash Ahmadian Romina Abachi Igor Gilitschenski Amir-massoud Farahmand 59 0 0 30 Jun 2023
Simplified Temporal Consistency Reinforcement Learning Yi Zhao Wenshuai Zhao Rinu Boney Arno Solin Joni Pajarinen OffRL 32 13 0 15 Jun 2023
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning Jialong Wu Haoyu Ma Chao Deng Mingsheng Long OffRL 38 25 0 29 May 2023
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation David Brandfonbrener Ofir Nachum Joan Bruna AI4CE 31 21 0 26 May 2023
Policy Gradient Methods in the Presence of Symmetries and State Abstractions Prakash Panangaden S. Rezaei-Shoshtari Rosie Zhao David Meger Doina Precup 38 2 0 09 May 2023
Hierarchical State Abstraction Based on Structural Information Principles Xianghua Zeng Hao Peng Angsheng Li Chunyang Liu Lifang He Philip S. Yu 36 18 0 24 Apr 2023
Accelerating exploration and representation learning with offline pre-training Bogdan Mazoure Jake Bruce Doina Precup Rob Fergus Ankit Anand OffRL 41 5 0 31 Mar 2023
Language-Driven Representation Learning for Robotics Siddharth Karamcheti Suraj Nair Annie S. Chen Thomas Kollar Chelsea Finn Dorsa Sadigh Percy Liang LM&Ro SSL 47 145 0 24 Feb 2023
Predictable MDP Abstraction for Unsupervised Model-Based RL Seohong Park Sergey Levine 26 9 0 08 Feb 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan Joshua Greaves Jesse Farebrother Mark Rowland Fabian Pedregosa Rishabh Agarwal Marc G. Bellemare 52 8 0 08 Dec 2022
Representation Learning for Continuous Action Spaces is Beneficial for Efficient Policy Learning Tingting Zhao Ying Wang Weidong Sun Yarui Chen Gang Niu Masashi Sugiyama 19 1 0 23 Nov 2022
Reward-Predictive Clustering Lucas Lehnert M. Frank Michael L. Littman OffRL 27 0 0 07 Nov 2022
On learning history based policies for controlling Markov decision processes Gandharv Patil Aditya Mahajan Doina Precup OffRL 21 5 0 06 Nov 2022
Disentangled (Un)Controllable Features Jacob E. Kooi Mark Hoogendoorn Vincent François-Lavet DRL 27 0 0 31 Oct 2022
On Many-Actions Policy Gradient Michal Nauman Marek Cygan 19 0 0 24 Oct 2022
Planning for Sample Efficient Imitation Learning Zhao-Heng Yin Weirui Ye Qifeng Chen Yang Gao OffRL 33 21 0 18 Oct 2022
Visuo-Tactile Transformers for Manipulation Yizhou Chen A. Sipos Mark Van der Merwe Nima Fazeli ViT 67 34 0 30 Sep 2022
Locally Constrained Representations in Reinforcement Learning Somjit Nath Rushiv Arora Samira Ebrahimi Kahou OOD OffRL 34 0 0 20 Sep 2022
Continuous MDP Homomorphisms and Homomorphic Policy Gradient S. Rezaei-Shoshtari Rosie Zhao Prakash Panangaden David Meger Doina Precup 35 18 0 15 Sep 2022
Sparsity Inducing Representations for Policy Decompositions Ashwin Khadke H. Geyer 21 1 0 15 Sep 2022
A model-based approach to meta-Reinforcement Learning: Transformers and tree search Brieuc Pinon Jean-Charles Delvenne Raphaël Jungers OffRL 40 3 0 24 Aug 2022
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Driving Haochen Liu Zhiyu Huang Xiaoyu Mo Chen Lv ViT OffRL 40 34 0 24 Aug 2022
Spectral Decomposition Representation for Reinforcement Learning Tongzheng Ren Tianjun Zhang Lisa Lee Joseph E. Gonzalez Dale Schuurmans Bo Dai OffRL 40 27 0 19 Aug 2022
Sampling Through the Lens of Sequential Decision Making J. Dou Alvin Pan Runxue Bao Haiyi Mao Lei Luo Zhi-Hong Mao 26 19 0 17 Aug 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning Shuang Qiu Lingxiao Wang Chenjia Bai Zhuoran Yang Zhaoran Wang SSL OffRL 26 32 0 29 Jul 2022
Making Linear MDPs Practical via Contrastive Representation Learning Tianjun Zhang Tongzheng Ren Mengjiao Yang Joseph E. Gonzalez Dale Schuurmans Bo Dai 25 44 0 14 Jul 2022
Unsupervised learning of observation functions in state-space models by nonparametric moment methods Qi An Yannis G. Kevrekidis Fei Lu Mauro Maggioni 20 2 0 12 Jul 2022
Masked World Models for Visual Control Younggyo Seo Danijar Hafner Hao Liu Fangchen Liu Stephen James Kimin Lee Pieter Abbeel OffRL 93 147 0 28 Jun 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni Dylan J. Foster Dipendra Kumar Misra A. Krishnamurthy John Langford OffRL 31 25 0 09 Jun 2022
Meta-Learning Parameterized Skills Haotian Fu Shangqun Yu Saket Tiwari Michael Littman George Konidaris 38 6 0 07 Jun 2022
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning Philippe Hansen-Estruch Amy Zhang Ashvin Nair Patrick Yin Sergey Levine AI4CE 35 28 0 27 Apr 2022
Understanding and Preventing Capacity Loss in Reinforcement Learning Clare Lyle Mark Rowland Will Dabney CLL 41 110 0 20 Apr 2022
Reinforcement Learning with Action-Free Pre-Training from Videos Younggyo Seo Kimin Lee Stephen James Pieter Abbeel SSL OnRL 23 119 0 25 Mar 2022
Transfer RL across Observation Feature Spaces via Model-Based Regularization Yanchao Sun Ruijie Zheng Xiyao Wang Andrew Cohen Furong Huang OOD OffRL 25 21 0 01 Jan 2022
Learning State Representations via Retracing in Reinforcement Learning Changmin Yu Dong Li Jianye Hao Jun Wang Neil Burgess 32 7 0 24 Nov 2021
A Free Lunch from the Noise: Provable and Practical Exploration for Representation Learning Tongzheng Ren Tianjun Zhang Csaba Szepesvári Bo Dai 27 19 0 22 Nov 2021
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data Mengjiao Yang Sergey Levine Ofir Nachum OffRL 41 42 0 27 Oct 2021