Hyperparameters in Reinforcement Learning and How To Tune Them

2 June 2023

Papers citing "Hyperparameters in Reinforcement Learning and How To Tune Them"

8 / 8 papers shown

Title
Hyperspherical Normalization for Scalable Deep Reinforcement Learning Hojoon Lee Youngdo Lee Takuma Seno Donghu Kim Peter Stone Jaegul Choo 63 1 0 24 Feb 2025
Neuroplastic Expansion in Deep Reinforcement Learning Jiashun Liu J. Obando-Ceron Aaron C. Courville L. Pan 31 3 0 10 Oct 2024
The Role of Deep Learning Regularizations on Actors in Offline RL Denis Tarasov Anja Surina Çağlar Gülçehre OffRL AI4CE 42 1 0 11 Sep 2024
ARES: Alternating Reinforcement Learning and Supervised Fine-Tuning for Enhanced Multi-Modal Chain-of-Thought Reasoning Through Diverse AI Feedback Ju-Seung Byun Jiyun Chun Jihyung Kil Andrew Perrault ReLM LRM 24 1 0 25 Jun 2024
Hierarchical Transformers are Efficient Meta-Reinforcement Learners Gresa Shala André Biedenkapp Josif Grabocka OffRL 14 4 0 09 Feb 2024
Dungeons and Data: A Large-Scale NetHack Dataset Eric Hambro Roberta Raileanu Dan Rothermel Vegard Mella Tim Rocktaschel Heinrich Küttler Naila Murray OffRL 121 18 0 01 Nov 2022
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization Marius Lindauer Katharina Eggensperger Matthias Feurer André Biedenkapp Difan Deng C. Benjamins Tim Ruhopf René Sass Frank Hutter 80 323 0 20 Sep 2021
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits Jack Parker-Holder Vu Nguyen Stephen J. Roberts OffRL 62 82 0 06 Feb 2020