Cover Image

Boosting Hierarchical Reinforcement Learning with Meta-Learning for Complex Task Adaptation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Khajooeinejad, Arash, Masoumi, Fatemeh Sadat, Chapariniya, Masoumeh
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

Meta Hierarchical Reinforcement Learning for Scalable Resource Management in O-RAN
by: Lotfi, Fatemeh, et al.
Published: (2025)

Task Specific Sharpness Aware O-RAN Resource Management using Multi Agent Reinforcement Learning
by: Lotfi, Fatemeh, et al.
Published: (2025)

A Reinforcement Learning-Based Task Mapping Method to Improve the Reliability of Clustered Manycores
by: Hossein-Khani, Fatemeh, et al.
Published: (2024)

Hypothesis Network Planned Exploration for Rapid Meta-Reinforcement Learning Adaptation
by: Jacobson, Maxwell Joseph, et al.
Published: (2023)

Hierarchical Meta-Reinforcement Learning via Automated Macro-Action Discovery
by: Cho, Minjae, et al.
Published: (2024)

Directed-MAML: Meta Reinforcement Learning Algorithm with Task-directed Approximation
by: Zhang, Yang, et al.
Published: (2025)

RL$^3$: Boosting Meta Reinforcement Learning via RL inside RL$^2$
by: Bhatia, Abhinav, et al.
Published: (2023)

Gradient Boosting Reinforcement Learning
by: Fuhrer, Benjamin, et al.
Published: (2024)

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks
by: Kim, Jeongmo, et al.
Published: (2025)

ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing
by: Lotfi, Fatemeh, et al.
Published: (2025)

Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning
by: Lu, Yuxiao, et al.
Published: (2023)

Meta Reinforcement Learning Approach for Adaptive Resource Optimization in O-RAN
by: Lotfi, Fatemeh, et al.
Published: (2024)

Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach
by: Rimon, Zohar, et al.
Published: (2022)

Memory Sequence Length of Data Sampling Impacts the Adaptation of Meta-Reinforcement Learning Agents
by: Zhang, Menglong, et al.
Published: (2024)

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
by: Qian, Fuyuan, et al.
Published: (2026)

Boosting Reinforcement Learning in 3D Visuospatial Tasks Through Human-Informed Curriculum Design
by: Solbach, Markus D., et al.
Published: (2025)

HU at SemEval-2024 Task 8A: Can Contrastive Learning Learn Embeddings to Detect Machine-Generated Text?
by: Dipta, Shubhashis Roy, et al.
Published: (2024)

Hierarchical Transformers are Efficient Meta-Reinforcement Learners
by: Shala, Gresa, et al.
Published: (2024)

TIMRL: A Novel Meta-Reinforcement Learning Framework for Non-Stationary and Multi-Task Environments
by: Qi, Chenyang, et al.
Published: (2025)

Set-based Meta-Interpolation for Few-Task Meta-Learning
by: Lee, Seanie, et al.
Published: (2022)

Meta-Learning Reinforcement Learning for Crypto-Return Prediction
by: Wang, Junqiao, et al.
Published: (2025)

Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation
by: Ambekar, Sameer, et al.
Published: (2025)

Task Scheduling & Forgetting in Multi-Task Reinforcement Learning
by: Speckmann, Marc, et al.
Published: (2025)

Adapt under Attack and Domain Shift: Unified Adversarial Meta-Learning and Domain Adaptation for Robust Automatic Modulation Classification
by: Owfi, Ali, et al.
Published: (2025)

Skill-Critic: Refining Learned Skills for Hierarchical Reinforcement Learning
by: Hao, Ce, et al.
Published: (2023)

Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning
by: Cherepanov, Egor, et al.
Published: (2025)

Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
by: Valencia, David, et al.
Published: (2024)

DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data
by: Ilaty, Arshia, et al.
Published: (2026)

How Should We Meta-Learn Reinforcement Learning Algorithms?
by: Goldie, Alexander David, et al.
Published: (2025)

Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent
by: Hoppmann, Björn, et al.
Published: (2026)

Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
by: Zhuang, Yuan, et al.
Published: (2026)

Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
by: Zhang, Hai, et al.
Published: (2024)

Task-Distributionally Robust Data-Free Meta-Learning
by: Hu, Zixuan, et al.
Published: (2023)

Boosting deep Reinforcement Learning using pretraining with Logical Options
by: Ye, Zihan, et al.
Published: (2026)

Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
by: Cipollone, Roberto, et al.
Published: (2025)

Deep Reinforcement Learning from Hierarchical Preference Design
by: Bukharin, Alexander, et al.
Published: (2023)

Group Fairness in Multi-Task Reinforcement Learning
by: Song, Kefan, et al.
Published: (2025)

Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
by: Lee, Daehee, et al.
Published: (2024)

DHP: Discrete Hierarchical Planning for Hierarchical Reinforcement Learning Agents
by: Sharma, Shashank, et al.
Published: (2025)

Efficient Multi-Task Reinforcement Learning with Cross-Task Policy Guidance
by: He, Jinmin, et al.
Published: (2025)