Copertina

Predictive Representations for Skill Transfer in Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Vereecken, Ruben, Dickens, Luke, Russo, Alessandra
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Neural DNF-MT: A Neuro-symbolic Approach for Learning Interpretable and Editable Policies
di: Baugh, Kexin Gu, et al.
Pubblicazione: (2025)

Disentangling Neural Disjunctive Normal Form Models
di: Baugh, Kexin Gu, et al.
Pubblicazione: (2025)

Learning Transferable Predictability Representations
di: Goswami, Diyali, et al.
Pubblicazione: (2026)

Evaluating the Robustness of Reinforcement Learning based Adaptive Traffic Signal Control
di: Kwesiga, Dickens, et al.
Pubblicazione: (2026)

Skill Transfer and Discovery for Sim-to-Real Learning: A Representation-Based Viewpoint
di: Ma, Haitong, et al.
Pubblicazione: (2024)

Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
di: Reizinger, Patrik, et al.
Pubblicazione: (2025)

Model-Free Active Exploration in Reinforcement Learning
di: Russo, Alessio, et al.
Pubblicazione: (2024)

Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
di: Wang, Min, et al.
Pubblicazione: (2025)

Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
di: Nottingham, Kolby, et al.
Pubblicazione: (2024)

UTOPYA: A Multimodal Deep Learning Framework for Physics-Informed Anomaly Detection and Time-Series Prediction
di: Pessoa, Robson W. S., et al.
Pubblicazione: (2026)

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning
di: Adaikkappan, Valliappan Chidambaram, et al.
Pubblicazione: (2026)

Outcome-based Reinforcement Learning to Predict the Future
di: Turtel, Benjamin, et al.
Pubblicazione: (2025)

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

SkillOrchestra: Learning to Route Agents via Skill Transfer
di: Wang, Jiayu, et al.
Pubblicazione: (2026)

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
di: Xia, Peng, et al.
Pubblicazione: (2026)

Adversarial Diffusion for Robust Reinforcement Learning
di: Foffano, Daniele, et al.
Pubblicazione: (2025)

Enabling Multi-Agent Transfer Reinforcement Learning via Scenario Independent Representation
di: Nipu, Ayesha Siddika, et al.
Pubblicazione: (2024)

Representational Transfer Learning for Matrix Completion
di: He, Yong, et al.
Pubblicazione: (2024)

Length Generalization with Log-Depth Recurrent Units
di: Pert, Charles, et al.
Pubblicazione: (2026)

Grounding Generated Videos in Feasible Plans via World Models
di: Ziakas, Christos, et al.
Pubblicazione: (2026)

Adaptive Active Learning for Regression via Reinforcement Learning
di: Nguyen, Simon D., et al.
Pubblicazione: (2026)

Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
di: Krishnamurthy, Vikram, et al.
Pubblicazione: (2026)

Skill-R1: Agent Skill Evolution via Reinforcement Learning
di: Vishe, Yash, et al.
Pubblicazione: (2026)

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
di: Tasse, Geraud Nangue, et al.
Pubblicazione: (2022)

The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning
di: Cunnington, Daniel, et al.
Pubblicazione: (2024)

SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization
di: Lu, Zhengxi, et al.
Pubblicazione: (2026)

LearnAD: Learning Interpretable Rules for Brain Networks in Alzheimer's Disease Classification
di: Andrews, Thomas, et al.
Pubblicazione: (2025)

Offline Multitask Representation Learning for Reinforcement Learning
di: Ishfaq, Haque, et al.
Pubblicazione: (2024)

Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics
di: Snow, Luke, et al.
Pubblicazione: (2023)

Model-Based Transfer Learning for Contextual Reinforcement Learning
di: Cho, Jung-Hoon, et al.
Pubblicazione: (2024)

Aligning Flow Map Policies with Optimal Q-Guidance
di: Ziakas, Christos, et al.
Pubblicazione: (2026)

Skills Regularized Task Decomposition for Multi-task Offline Reinforcement Learning
di: Yoo, Minjong, et al.
Pubblicazione: (2024)

Feasibility Consistent Representation Learning for Safe Reinforcement Learning
di: Cen, Zhepeng, et al.
Pubblicazione: (2024)

Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning
di: Hu, Jiaheng, et al.
Pubblicazione: (2024)

Offline Reinforcement Learning with Discrete Diffusion Skills
di: Qiao, RuiXi, et al.
Pubblicazione: (2025)

Learning to Transfer Human Hand Skills for Robot Manipulations
di: Park, Sungjae, et al.
Pubblicazione: (2025)

Topotein: Topological Deep Learning for Protein Representation Learning
di: Wang, Zhiyu, et al.
Pubblicazione: (2025)

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning
di: Shen, Junhao, et al.
Pubblicazione: (2026)

Materials Representation and Transfer Learning for Multi-Property Prediction
di: Kong, Shufeng, et al.
Pubblicazione: (2021)

Skill-based Safe Reinforcement Learning with Risk Planning
di: Zhang, Hanping, et al.
Pubblicazione: (2025)