When Is Partially Observable Reinforcement Learning Not Scary?

19 April 2022

Papers citing "When Is Partially Observable Reinforcement Learning Not Scary?"

24 / 24 papers shown

Title
Uncertainty Representations in State-Space Layers for Deep Reinforcement Learning under Partial Observability Carlos E. Luis A. Bottero Julia Vinogradska Felix Berkenkamp Jan Peters 78 1 0 20 Feb 2025
The Central Role of the Loss Function in Reinforcement Learning Kaiwen Wang Nathan Kallus Wen Sun OffRL 62 7 0 19 Sep 2024
Value of Information and Reward Specification in Active Inference and POMDPs Ran Wei 57 3 0 13 Aug 2024
On shallow planning under partial observability Randy Lefebvre Audrey Durand OffRL 39 0 0 22 Jul 2024
Preference Elicitation for Offline Reinforcement Learning Alizée Pace Bernhard Schölkopf Gunnar Rätsch Giorgia Ramponi OffRL 69 1 0 26 Jun 2024
DPO Meets PPO: Reinforced Token Optimization for RLHF Han Zhong Zikang Shan Guhao Feng Li Zhao Di He Jiang Bian Di He Jiang Bian Liwei Wang 57 57 0 29 Apr 2024
Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Yu Chen Xiangcheng Zhang Siwei Wang Longbo Huang 42 3 0 28 Feb 2024
On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation Yuheng Zhang Nan Jiang OffRL 29 4 0 22 Feb 2024
Provable Representation with Efficient Planning for Partial Observable Reinforcement Learning Hongming Zhang Tongzheng Ren Chenjun Xiao Dale Schuurmans Bo Dai 45 3 0 20 Nov 2023
Posterior Sampling-based Online Learning for Episodic POMDPs Dengwang Tang Dongze Ye Rahul Jain A. Nayyar Pierluigi Nuzzo OffRL 51 0 0 16 Oct 2023
Transformers in Reinforcement Learning: A Survey Pranav Agarwal A. Rahman P. St-Charles Simon J. D. Prince Samira Ebrahimi Kahou OffRL 26 19 0 12 Jul 2023
Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP Jiacheng Guo Zihao Li Huazheng Wang Mengdi Wang Zhuoran Yang Xuezhou Zhang 32 5 0 21 Jun 2023
On the Provable Advantage of Unsupervised Pretraining Jiawei Ge Shange Tang Jianqing Fan Chi Jin SSL 33 16 0 02 Mar 2023
Learning in POMDPs is Sample-Efficient with Hindsight Observability Jonathan Lee Alekh Agarwal Christoph Dann Tong Zhang 34 19 0 31 Jan 2023
Eluder-based Regret for Stochastic Contextual MDPs Orin Levy Asaf B. Cassel Alon Cohen Yishay Mansour 33 5 0 27 Nov 2022
Tractable Optimality in Episodic Latent MABs Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 50 3 0 05 Oct 2022
Reward-Mixing MDPs with a Few Latent Contexts are Learnable Jeongyeol Kwon Yonathan Efroni C. Caramanis Shie Mannor 31 5 0 05 Oct 2022
PAC Reinforcement Learning for Predictive State Representations Wenhao Zhan Masatoshi Uehara Wen Sun Jason D. Lee 33 38 0 12 Jul 2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun 60 6 0 24 Jun 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems Masatoshi Uehara Ayush Sekhari Jason D. Lee Nathan Kallus Wen Sun OffRL 49 31 0 24 Jun 2022
Sample-Efficient Reinforcement Learning of Partially Observable Markov Games Qinghua Liu Csaba Szepesvári Chi Jin 40 20 0 02 Jun 2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes Miao Lu Yifei Min Zhaoran Wang Zhuoran Yang OffRL 57 22 0 26 May 2022
Provably Efficient Reinforcement Learning with Linear Function Approximation Under Adaptivity Constraints Chi Jin Zhuoran Yang Zhaoran Wang OffRL 122 166 0 06 Jan 2021
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan H. Zha 25 21 0 17 Apr 2020