:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Han, Shuai, Dastani, Mehdi, Wang, Shihan
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2401.14226
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Credit Assignment and Efficient Exploration based on Influence Scope in Multi-agent Reinforcement Learning
par: Han, Shuai, et autres
Publié: (2025)

Neuro-symbolic Action Masking for Deep Reinforcement Learning
par: Han, Shuai, et autres
Publié: (2026)

A Survey of Multi-Agent Deep Reinforcement Learning with Communication
par: Zhu, Changxi, et autres
Publié: (2022)

Reducing Variance Caused by Communication in Decentralized Multi-agent Deep Reinforcement Learning
par: Zhu, Changxi, et autres
Publié: (2025)

Learning Communication Skills in Multi-task Multi-agent Deep Reinforcement Learning
par: Zhu, Changxi, et autres
Publié: (2025)

Pushdown Reward Machines for Reinforcement Learning
par: Varricchione, Giovanni, et autres
Publié: (2025)

Balancing the Scales: Reinforcement Learning for Fair Classification
par: Eshuijs, Leon, et autres
Publié: (2024)

Maximally Permissive Reward Machines
par: Varricchione, Giovanni, et autres
Publié: (2024)

Sample-Efficient Reinforcement Learning from Human Feedback via Information-Directed Sampling
par: Qi, Han, et autres
Publié: (2025)

Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision Processes
par: Rojas, Juan Sebastian, et autres
Publié: (2024)

Self-Composing Policies for Scalable Continual Reinforcement Learning
par: Malagón, Mikel, et autres
Publié: (2025)

Distributional Dataset Distillation with Subtask Decomposition
par: Qin, Tian, et autres
Publié: (2024)

Fundamental Properties of Causal Entropy and Information Gain
par: Simoes, Francisco N. F. Q., et autres
Publié: (2024)

Causal Entropy and Information Gain for Measuring Causal Control
par: Simoes, Francisco Nunes Ferreira Quialheiro, et autres
Publié: (2023)

Provably Sample-Efficient Robust Reinforcement Learning with Average Reward
par: Roch, Zachary, et autres
Publié: (2025)

Subtask-Aware Visual Reward Learning from Segmented Demonstrations
par: Kim, Changyeon, et autres
Publié: (2025)

The Causal Information Bottleneck and Optimal Causal Variable Abstractions
par: Simoes, Francisco N. F. Q., et autres
Publié: (2024)

Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance
par: Ding, Shutong, et autres
Publié: (2026)

SEAR: Sample Efficient Action Chunking Reinforcement Learning
par: Nagy, C. F. Maximilian, et autres
Publié: (2026)

Identifying Selections for Unsupervised Subtask Discovery
par: Qiu, Yiwen, et autres
Publié: (2024)

Investigating the Robustness of Subtask Distillation under Spurious Correlation
par: Chormai, Pattarawat, et autres
Publié: (2026)

The Minimal Search Space for Conditional Causal Bandits
par: Simoes, Francisco N. F. Q., et autres
Publié: (2025)

Succeed or Learn Slowly: Sample Efficient Off-Policy Reinforcement Learning for Mobile App Control
par: Papoudakis, Georgios, et autres
Publié: (2025)

Communication-Efficient and Interoperable Distributed Learning
par: Krouka, Mounssif, et autres
Publié: (2025)

MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization
par: Wang, Ziqing, et autres
Publié: (2026)

From Generative to Episodic: Sample-Efficient Replicable Reinforcement Learning
par: Hopkins, Max, et autres
Publié: (2025)

AutoTriton: Automatic Triton Programming with Reinforcement Learning in LLMs
par: Li, Shangzhan, et autres
Publié: (2025)

Sample-Efficient Constrained Reinforcement Learning with General Parameterization
par: Mondal, Washim Uddin, et autres
Publié: (2024)

Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning
par: Wan, Jia, et autres
Publié: (2024)

Quantum Boltzmann Machines for Sample-Efficient Reinforcement Learning
par: Gerlach, Thore, et autres
Publié: (2025)

Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge
par: Alharbi, Meshal, et autres
Publié: (2023)

Sample-Efficient Reinforcement Learning of Koopman eNMPC
par: Mayfrank, Daniel, et autres
Publié: (2025)

Sample Efficient Active Algorithms for Offline Reinforcement Learning
par: Roy, Soumyadeep, et autres
Publié: (2026)

CADENT: Gated Hybrid Distillation for Sample-Efficient Transfer in Reinforcement Learning
par: Alinejad, Mahyar, et autres
Publié: (2026)

Train Less, Learn More: Adaptive Efficient Rollout Optimization for Group-Based Reinforcement Learning
par: Zhang, Zhi, et autres
Publié: (2026)

Sample-Efficient Policy Constraint Offline Deep Reinforcement Learning based on Sample Filtering
par: Chen, Yuanhao, et autres
Publié: (2025)

Speculative Sampling with Reinforcement Learning
par: Wang, Chenan, et autres
Publié: (2026)

Sample-Efficient Tabular Self-Play for Offline Robust Reinforcement Learning
par: Li, Na, et autres
Publié: (2025)

GCHR : Goal-Conditioned Hindsight Regularization for Sample-Efficient Reinforcement Learning
par: Lei, Xing, et autres
Publié: (2025)

Instance-Prototype Affinity Learning for Non-Exemplar Continual Graph Learning
par: Song, Lei, et autres
Publié: (2025)