How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments

21 June 2018

Papers citing "How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments"

21 / 21 papers shown

Title
Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning Rémy Hosseinkhan Boucher Onofrio Semeraro L. Mathelin 87 0 0 28 Jan 2025
Reproducibility in Machine Learning-based Research: Overview, Barriers and Drivers Harald Semmelrock Tony Ross-Hellauer Simone Kopeinik Dieter Theiler Armin Haberl Stefan Thalmann Dominik Kowald 65 7 0 20 Jun 2024
AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents Christopher Rawles Sarah Clinckemaillie Yifan Chang Jonathan Waltz Gabrielle Lau ... Daniel Toyama Robert Berry Divya Tyamagundlu Timothy Lillicrap Oriana Riva LLMAG 72 44 0 23 May 2024
Deep Q-Network Based Decision Making for Autonomous Driving M. Ronecker Yuan-xian Zhu 27 32 0 21 Mar 2023
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems Megan M. Baker Alexander New Mario Aguilar-Simon Ziad Al-Halah Sébastien M. R. Arnold ... Zifan Xu A. Yanguas-Gil Harel Yedidsion Shangqun Yu Gautam K. Vallabha 35 16 0 18 Jan 2023
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL R. Gorsane Omayma Mahjoub Ruan de Kock Roland Dubb Siddarth S. Singh Arnu Pretorius OffRL 44 50 0 21 Sep 2022
How stable are Transferability Metrics evaluations? A. Agostinelli Michal Pándy J. Uijlings Thomas Mensink V. Ferrari 37 23 0 04 Apr 2022
Towards Training Reproducible Deep Learning Models Boyuan Chen Mingzhi Wen Yong Shi Dayi Lin Gopi Krishnan Rajbahadur Zhen Ming Z. Jiang SyDa 23 37 0 04 Feb 2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems Jack Parker-Holder Raghunandan Rajan Xingyou Song André Biedenkapp Yingjie Miao ... Vu-Linh Nguyen Roberto Calandra Aleksandra Faust Frank Hutter Marius Lindauer AI4CE 38 100 0 11 Jan 2022
Deep Reinforcement Learning at the Edge of the Statistical Precipice Rishabh Agarwal Max Schwarzer Pablo Samuel Castro Aaron Courville Marc G. Bellemare OffRL 61 643 0 30 Aug 2021
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL Clément Romac Rémy Portelas Katja Hofmann Pierre-Yves Oudeyer 29 21 0 17 Mar 2021
Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research J. Obando-Ceron Pablo Samuel Castro OffRL 20 105 0 20 Nov 2020
Dirichlet policies for reinforced factor portfolios Eric André Guillaume Coqueret 25 7 0 10 Nov 2020
Control with adaptive Q-learning J. Araújo Mário A. T. Figueiredo M. Botto 33 2 0 03 Nov 2020
Intrinsic Robotic Introspection: Learning Internal States From Neuron Activations N. Pitsillos Ameya Pore B. S. Jensen G. Aragon-Camarasa 15 3 0 03 Nov 2020
How to Make Deep RL Work in Practice Nirnai Rao Elie Aljalbout Axel Sauer Sami Haddadin OffRL 29 11 0 25 Oct 2020
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning L. Hertel Pierre Baldi D. Gillen BDL 31 12 0 29 Jul 2020
On the Sensory Commutativity of Action Sequences for Embodied Agents Hugo Caselles-Dupré Michael Garcia Ortiz David Filliat 21 4 0 13 Feb 2020
On the Role of Weight Sharing During Deep Option Learning Matthew D Riemer Ignacio Cases Clemens Rosenbaum Miao Liu Gerald Tesauro OffRL 14 18 0 31 Dec 2019
Investigating Generalisation in Continuous Deep Reinforcement Learning Chenyang Zhao Olivier Sigaud F. Stulp Timothy M. Hospedales OffRL 22 48 0 19 Feb 2019
Deterministic Implementations for Reproducibility in Deep Reinforcement Learning P. Nagarajan Garrett A. Warnell Peter Stone 22 51 0 15 Sep 2018