Cover Image

The Role of Deep Learning Regularizations on Actors in Offline RL

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tarasov, Denis, Surina, Anja, Gulcehre, Caglar
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
by: Terekhov, Mikhail, et al.
Published: (2024)

Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning?
by: Tarasov, Denis, et al.
Published: (2024)

Yes, Q-learning Helps Offline In-Context RL
by: Tarasov, Denis, et al.
Published: (2025)

Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
by: Luo, Yu, et al.
Published: (2024)

Flow Actor-Critic for Offline Reinforcement Learning
by: Chae, Jongseong, et al.
Published: (2026)

Simple Hierarchical Planning with Diffusion
by: Chen, Chang, et al.
Published: (2024)

Control Tax: The Price of Keeping AI in Check
by: Terekhov, Mikhail, et al.
Published: (2025)

RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization
by: Fukazawa, Kai, et al.
Published: (2025)

PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
by: Chen, Chang, et al.
Published: (2024)

FORLER: Federated Offline Reinforcement Learning with Q-Ensemble and Actor Rectification
by: Qiao, Nan, et al.
Published: (2026)

Budgeting Counterfactual for Offline RL
by: Liu, Yao, et al.
Published: (2023)

Is Value Learning Really the Main Bottleneck in Offline RL?
by: Park, Seohong, et al.
Published: (2024)

Offline Actor-Critic Reinforcement Learning Scales to Large Models
by: Springenberg, Jost Tobias, et al.
Published: (2024)

Proximal Action Replacement for Behavior Cloning Actor-Critic in Offline Reinforcement Learning
by: Dong, Jinzong, et al.
Published: (2026)

Mutual Information Regularized Offline Reinforcement Learning
by: Ma, Xiao, et al.
Published: (2022)

Augmenting Offline RL with Unlabeled Data
by: Wang, Zhao, et al.
Published: (2024)

Selective Uncertainty Propagation in Offline RL
by: Krishnamurthy, Sanath Kumar, et al.
Published: (2023)

Decoupled Prioritized Resampling for Offline RL
by: Yue, Yang, et al.
Published: (2023)

An Empirical Study on the Effectiveness of Incorporating Offline RL As Online RL Subroutines
by: Su, Jianhai, et al.
Published: (2025)

Entropy-Regularized Adjoint Matching for Offline Reinforcement Learning
by: Ghanem, Abdelghani, et al.
Published: (2026)

Mildly Conservative Regularized Evaluation for Offline Reinforcement Learning
by: Chen, Haohui, et al.
Published: (2025)

Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
by: Mark, Max Sobol, et al.
Published: (2024)

Double Actor-Critic with TD Error-Driven Regularization in Reinforcement Learning
by: Chen, Haohui, et al.
Published: (2024)

Are Expressive Models Truly Necessary for Offline RL?
by: Wang, Guan, et al.
Published: (2024)

OGBench: Benchmarking Offline Goal-Conditioned RL
by: Park, Seohong, et al.
Published: (2024)

A Tractable Inference Perspective of Offline RL
by: Liu, Xuejie, et al.
Published: (2023)

Design Considerations in Offline Preference-based RL
by: Agarwal, Alekh, et al.
Published: (2025)

SMAC: Score-Matched Actor-Critics for Robust Offline-to-Online Transfer
by: de Lara, Nathan Samuel, et al.
Published: (2026)

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
by: Gao, Chen-Xiao, et al.
Published: (2025)

OMG-RL:Offline Model-based Guided Reward Learning for Heparin Treatment
by: Lim, Yooseok, et al.
Published: (2024)

Offline Multi-task Transfer RL with Representational Penalization
by: Bose, Avinandan, et al.
Published: (2024)

Scalable Offline Model-Based RL with Action Chunks
by: Park, Kwanyoung, et al.
Published: (2025)

Self-Recognition in Language Models
by: Davidson, Tim R., et al.
Published: (2024)

Revisiting Mixture Policies in Entropy-Regularized Actor-Critic
by: He, Jiamin, et al.
Published: (2026)

In-Dataset Trajectory Return Regularization for Offline Preference-based Reinforcement Learning
by: Tu, Songjun, et al.
Published: (2024)

Offline vs. Online Learning in Model-based RL: Lessons for Data Collection Strategies
by: Chen, Jiaqi, et al.
Published: (2025)

SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation
by: Kiyohara, Haruka, et al.
Published: (2023)

Critic-Driven Voronoi-Quantization for Distilling Deep RL Policies to Explainable Models
by: Deproost, Senne, et al.
Published: (2026)

Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution
by: Deproost, Senne, et al.
Published: (2024)

From Markov to Laplace: How Mamba In-Context Learns Markov Chains
by: Bondaschi, Marco, et al.
Published: (2025)