SCOPE-RL: A Python Library for Offline Reinforcement Learning and
Off-Policy Evaluation

SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation

30 November 2023

Haruka Kiyohara

Kazuhide Nakata

Papers citing "SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation"

10 / 10 papers shown

Title
Prompt Optimization with Logged Bandit Data Haruka Kiyohara Daniel Yiming Cao Yuta Saito Thorsten Joachims 61 0 0 03 Apr 2025
Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol Pai Liu Lingfeng Zhao Shivangi Agarwal Jinghan Liu Audrey Huang P. Amortila Nan Jiang OODD OffRL 90 0 0 11 Feb 2025
Quantile Off-Policy Evaluation via Deep Conditional Generative Learning Yang Xu C. Shi S. Luo Lan Wang R. Song OffRL 19 4 0 29 Dec 2022
CORL: Research-oriented Deep Offline Reinforcement Learning Library Denis Tarasov Alexander Nikulin Dmitry Akimov Vladislav Kurenkov Sergey Kolesnikov OffRL 46 78 0 13 Oct 2022
Off-Policy Risk Assessment in Markov Decision Processes Audrey Huang Liu Leqi Zachary Chase Lipton Kamyar Azizzadenesheli OffRL 10 8 0 21 Sep 2022
SOPE: Spectrum of Off-Policy Estimators C. J. Yuan Yash Chandak S. Giguere Philip S. Thomas S. Niekum OffRL 31 5 0 06 Nov 2021
d3rlpy: An Offline Deep Reinforcement Learning Library Takuma Seno M. Imai OffRL GP 57 99 0 06 Nov 2021
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning Rongjun Qin Songyi Gao Xingyuan Zhang Zhen Xu Shengkai Huang Zewen Li Weinan Zhang Yang Yu OffRL 132 76 0 01 Feb 2021
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 329 1,944 0 04 May 2020
Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes Nathan Kallus Masatoshi Uehara OffRL 31 180 0 22 Aug 2019