Generalization and Exploration via Randomized Value Functions

4 February 2014

Papers citing "Generalization and Exploration via Randomized Value Functions"

50 / 94 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 99 3 0 29 Apr 2025
Look Before Leap: Look-Ahead Planning with Uncertainty in Reinforcement Learning Yongshuai Liu Xin Liu 103 1 0 26 Mar 2025
Minimax Optimal Reinforcement Learning with Quasi-Optimism Harin Lee Min-hwan Oh OffRL 66 1 0 02 Mar 2025
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic Stefano Viel Luca Viano Volkan Cevher 121 1 0 27 Feb 2025
Reinforcement Learning on Dyads to Enhance Medication Adherence Ziping Xu Hinal Jajal S. Choi Inbal Nahum-Shani Guy Shani Alexandra M. Psihogios Pei-Yao Hung Susan Murphy 76 0 0 06 Feb 2025
EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning Siddharth Aravindan Dixant Mittal Wee Sun Lee BDL 98 0 0 17 Jan 2025
A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals Grace Liu Michael Tang Benjamin Eysenbach OffRL 79 1 0 11 Aug 2024
Random Latent Exploration for Deep Reinforcement Learning Srinath Mahankali Zhang-Wei Hong Ayush Sekhari Alexander Rakhlin Pulkit Agrawal 64 3 0 18 Jul 2024
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback Asaf B. Cassel Haipeng Luo Aviv A. Rosenberg Dmitry Sotnikov OffRL 52 4 0 13 May 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li Jiawei Xu Lei Han Zhi-Quan Luo BDL OffRL 38 5 0 05 Feb 2024
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning Guojian Wang Faguo Wu Xiao Zhang Ning Guo Zhiming Zheng 46 3 0 27 Dec 2023
Inverse Decision Modeling: Learning Interpretable Representations of Behavior Daniel Jarrett Alihan Huyuk M. Schaar AI4CE 35 27 0 28 Oct 2023
Dyadic Reinforcement Learning Shuangning Li L. Niell S. Choi Inbal Nahum-Shani Guy Shani Susan Murphy OffRL 33 2 0 15 Aug 2023
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq Qingfeng Lan Pan Xu A. R. Mahmood Doina Precup Anima Anandkumar Kamyar Azizzadenesheli BDL OffRL 35 20 0 29 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 42 8 0 05 May 2023
VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation Thanh Nguyen-Tang R. Arora OffRL 58 5 0 24 Feb 2023
Reinforcement Learning in a Birth and Death Process: Breaking the Dependence on the State Space Jonatha Anselmi B. Gaujal Louis-Sébastien Rebuffi 51 2 0 21 Feb 2023
Efficient Planning in Combinatorial Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Volodymyr Tkachuk Seyed Alireza Bakhtiari Johannes Kirschner Matej Jusup Ilija Bogunovic Csaba Szepesvári 46 5 0 08 Feb 2023
Data-pooling Reinforcement Learning for Personalized Healthcare Intervention Xinyun Chen P. Shi Shanwen Pu OffRL 35 4 0 16 Nov 2022
Foundation Models for Semantic Novelty in Reinforcement Learning Tarun Gupta Peter Karkus Tong Che Danfei Xu Marco Pavone VLM OffRL LRM 50 7 0 09 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 47 4 0 30 Oct 2022
Planning to the Information Horizon of BAMDPs via Epistemic State Abstraction Dilip Arumugam Satinder Singh 49 3 0 30 Oct 2022
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games Wei Xiong Han Zhong Chengshuai Shi Cong Shen Tong Zhang 69 18 0 04 Oct 2022
Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks Litian Liang Yaosheng Xu Stephen Marcus McAleer Dailin Hu Alexander Ihler Pieter Abbeel Roy Fox OOD 46 18 0 16 Sep 2022
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann M. Mohri Tong Zhang Julian Zimmert OffRL 26 33 0 23 Aug 2022
Model-based RL with Optimistic Posterior Sampling: Structural Conditions and Sample Complexity Alekh Agarwal Tong Zhang 59 22 0 15 Jun 2022
Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement Learning Nicolas Castanet Sylvain Lamprier Olivier Sigaud 30 3 0 14 Jun 2022
Exploration in Deep Reinforcement Learning: A Survey Pawel Ladosz Lilian Weng Minwoo Kim H. Oh OffRL 33 330 0 02 May 2022
Provably Efficient Kernelized Q-Learning Shuang Liu H. Su MLT 49 4 0 21 Apr 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency Qi Cai Zhuoran Yang Zhaoran Wang 43 14 0 20 Apr 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets Yifei Min Tianhao Wang Ruitu Xu Zhaoran Wang Michael I. Jordan Zhuoran Yang 43 21 0 07 Mar 2022
Improving the Diversity of Bootstrapped DQN by Replacing Priors With Noise Li Meng Morten Goodwin Anis Yazidi P. Engelstad 35 4 0 02 Mar 2022
Improved Regret for Differentially Private Exploration in Linear MDP Dung Daniel Ngo G. Vietri Zhiwei Steven Wu 40 8 0 02 Feb 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching Gen Li Junbo Li Anmol Kabra Nathan Srebro Zhaoran Wang Zhuoran Yang 37 4 0 28 Dec 2021
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval Dingrong Wang Hitesh Sapkota Xumin Liu Qi Yu 50 4 0 21 Nov 2021
Safe Policy Optimization with Local Generalized Linear Function Approximations Akifumi Wachi Yunyue Wei Yanan Sui OffRL 38 10 0 09 Nov 2021
Perturbational Complexity by Distribution Mismatch: A Systematic Analysis of Reinforcement Learning in Reproducing Kernel Hilbert Space Jihao Long Jiequn Han 36 6 0 05 Nov 2021
The Value of Information When Deciding What to Learn Dilip Arumugam Benjamin Van Roy 42 12 0 26 Oct 2021
Exploring More When It Needs in Deep Reinforcement Learning Youtian Guo Qitong Gao 18 0 0 28 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain Jianye Hao Tianpei Yang Hongyao Tang Chenjia Bai Jinyi Liu Zhaopeng Meng Peng Liu Zhen Wang OffRL 41 94 0 14 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning Susan Amin Maziar Gomrokchi Harsh Satija H. V. Hoof Doina Precup OffRL 43 81 0 01 Sep 2021
Randomized Exploration for Reinforcement Learning with General Value Function Approximation Haque Ishfaq Qiwen Cui V. Nguyen Alex Ayoub Zhuoran Yang Zhaoran Wang Doina Precup Lin F. Yang 40 43 0 15 Jun 2021
Sample-Efficient Reinforcement Learning Is Feasible for Linearly Realizable MDPs with Limited Revisiting Gen Li Yuxin Chen Yuejie Chi Yuantao Gu Yuting Wei OffRL 37 28 0 17 May 2021
Beyond Fine-Tuning: Transferring Behavior in Reinforcement Learning Victor Campos Pablo Sprechmann Steven Hansen André Barreto Steven Kapturowski Alex Vitvitskyi Adria Puigdomenech Badia Charles Blundell OffRL OnRL 46 25 0 24 Feb 2021
Learning Adversarial Markov Decision Processes with Delayed Feedback Tal Lancewicki Aviv A. Rosenberg Yishay Mansour 43 32 0 29 Dec 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces Zhuoran Yang Chi Jin Zhaoran Wang Mengdi Wang Michael I. Jordan 47 18 0 09 Nov 2020
Control with adaptive Q-learning J. Araújo Mário A. T. Figueiredo M. Botto 38 2 0 03 Nov 2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration Priyank Agrawal Jinglin Chen Nan Jiang 42 19 0 23 Oct 2020
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning Tarun Gupta Anuj Mahajan Bei Peng Wendelin Bohmer Shimon Whiteson OffRL 24 50 0 06 Oct 2020
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 41 7 0 05 Oct 2020