Cover Image

Active Reinforcement Learning Strategies for Offline Policy Improvement

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dukkipati, Ambedkar, Ayyagari, Ranga Shaarad, Dasgupta, Bodhisattwa, Dutta, Parag, Onteru, Prabhas Reddy
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Temporal Abstraction in Reinforcement Learning with Offline Data
by: Ayyagari, Ranga Shaarad, et al.
Published: (2024)

Markov Decision Processes under External Temporal Processes
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)

Predictive AI with External Knowledge Infusion: Datasets and Benchmarks for Stock Markets
by: Dukkipati, Ambedkar, et al.
Published: (2025)

Emergent Natural Language with Communication Games for Improving Image Captioning Capabilities without Additional Data
by: Dutta, Parag, et al.
Published: (2025)

Sample Efficient Active Algorithms for Offline Reinforcement Learning
by: Roy, Soumyadeep, et al.
Published: (2026)

Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks
by: Gracious, Tony, et al.
Published: (2024)

Neural Temporal Point Processes for Forecasting Directional Relations in Evolving Hypergraphs
by: Gracious, Tony, et al.
Published: (2023)

Epistemic Robust Offline Reinforcement Learning
by: Chenreddy, Abhilash Reddy, et al.
Published: (2026)

Policy Improvement Reinforcement Learning
by: Wang, Huaiyang, et al.
Published: (2026)

Hypercube Policy Regularization Framework for Offline Reinforcement Learning
by: Shen, Yi, et al.
Published: (2024)

Hierarchical Subspaces of Policies for Continual Offline Reinforcement Learning
by: Kobanda, Anthony, et al.
Published: (2024)

Mildly Constrained Evaluation Policy for Offline Reinforcement Learning
by: Xu, Linjie, et al.
Published: (2023)

Distorted Distributional Policy Evaluation for Offline Reinforcement Learning
by: Iwaki, Ryo, et al.
Published: (2026)

Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning
by: Jing, Tan, et al.
Published: (2025)

Active Advantage-Aligned Online Reinforcement Learning with Offline Data
by: Liu, Xuefeng, et al.
Published: (2025)

Offline Reinforcement Learning with Generative Trajectory Policies
by: Feng, Xinsong, et al.
Published: (2025)

Policy-regularized Offline Multi-objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)

Policy-Based Trajectory Clustering in Offline Reinforcement Learning
by: Hu, Hao, et al.
Published: (2025)

Evaluation-Time Policy Switching for Offline Reinforcement Learning
by: Neggatu, Natinael Solomon, et al.
Published: (2025)

Incentivizing Safer Actions in Policy Optimization for Constrained Reinforcement Learning
by: Hazra, Somnath, et al.
Published: (2025)

Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
by: Koirala, Prajwal, et al.
Published: (2024)

A Non-Monolithic Policy Approach of Offline-to-Online Reinforcement Learning
by: Kim, JaeYoon, et al.
Published: (2024)

Diffusion Policies for Risk-Averse Behavior Modeling in Offline Reinforcement Learning
by: Chen, Xiaocong, et al.
Published: (2024)

Constrained Policy Optimization with Explicit Behavior Density for Offline Reinforcement Learning
by: Zhang, Jing, et al.
Published: (2023)

Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning
by: Khattar, Vanshaj, et al.
Published: (2024)

Preferred-Action-Optimized Diffusion Policies for Offline Reinforcement Learning
by: Zhang, Tianle, et al.
Published: (2024)

Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning
by: Chemingui, Yassine, et al.
Published: (2024)

To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learning
by: Ma, Tao, et al.
Published: (2024)

Policy Constraint by Only Support Constraint for Offline Reinforcement Learning
by: Gao, Yunkai, et al.
Published: (2025)

Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data
by: Madhow, Sunil, et al.
Published: (2023)

When is Offline Policy Selection Sample Efficient for Reinforcement Learning?
by: Liu, Vincent, et al.
Published: (2023)

Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning
by: Hu, Jifeng, et al.
Published: (2025)

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

Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
by: Kang, Hyungkyu, et al.
Published: (2025)

TEA: Trajectory Encoding Augmentation for Robust and Transferable Policies in Offline Reinforcement Learning
by: Ormancı, Batıkan Bora, et al.
Published: (2024)

Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimization
by: Yuan, Haochen, et al.
Published: (2025)

CODA: Coordination via On-Policy Diffusion for Multi-Agent Offline Reinforcement Learning
by: Hedman, Marcel, et al.
Published: (2026)

Blending Imitation and Reinforcement Learning for Robust Policy Improvement
by: Liu, Xuefeng, et al.
Published: (2023)

Rule-Guided Reinforcement Learning Policy Evaluation and Improvement
by: Tappler, Martin, et al.
Published: (2025)

Robust Offline Active Learning on Graphs
by: Wu, Yuanchen, et al.
Published: (2024)