:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Ghasemi, Majid, Moosavi, Amir Hossein, Ebrahimi, Dariush
Formato:	Preprint
Publicado:	2024
Materias:	Artificial Intelligence Machine Learning
Acceso en línea:	https://arxiv.org/abs/2411.18892
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Introduction to Reinforcement Learning
por: Ghasemi, Majid, et al.
Publicado: (2024)

Learning When to Trust in Contextual Bandits
por: Ghasemi, Majid, et al.
Publicado: (2026)

A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
por: Qing, Yunpeng, et al.
Publicado: (2022)

A Comprehensive Survey on Inverse Constrained Reinforcement Learning: Definitions, Progress and Challenges
por: Liu, Guiliang, et al.
Publicado: (2024)

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

Quantum-Efficient Reinforcement Learning Solutions for Last-Mile On-Demand Delivery
por: Moosavi, Farzan, et al.
Publicado: (2025)

Continual Learning of Large Language Models: A Comprehensive Survey
por: Shi, Haizhou, et al.
Publicado: (2024)

Locally Constrained Representations in Reinforcement Learning
por: Nath, Somjit, et al.
Publicado: (2022)

Environment-Aware Transfer Reinforcement Learning for Sustainable Beam Selection
por: Salami, Dariush, et al.
Publicado: (2025)

The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
por: Park, Giseung, et al.
Publicado: (2024)

Multi-agent Reinforcement Learning: A Comprehensive Survey
por: Huh, Dom, et al.
Publicado: (2023)

A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges
por: Zare, Maryam, et al.
Publicado: (2023)

A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications
por: Mu, Siyuan, et al.
Publicado: (2025)

A Comprehensive Survey of Deep Learning for Time Series Forecasting: Architectural Diversity and Open Challenges
por: Kim, Jongseon, et al.
Publicado: (2024)

The Terminal Representation in Reinforcement Learning
por: Esterhuysen, Amir, et al.
Publicado: (2026)

A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions
por: Yu, Zhiyin, et al.
Publicado: (2026)

Label-Free Reinforcement Learning via Cross-Model Entropy
por: Gorbett, Matt, et al.
Publicado: (2026)

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

A Survey of Continual Reinforcement Learning
por: Pan, Chaofan, et al.
Publicado: (2025)

Unsupervised Feature Selection to Identify Important ICD-10 Codes for Machine Learning: A Case Study on a Coronary Artery Disease Patient Cohort
por: Ghasemi, Peyman, et al.
Publicado: (2023)

Toward Virtuous Reinforcement Learning: A Critique and Roadmap
por: Ghasemi, Majid, et al.
Publicado: (2025)

Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges
por: van der Sar, Erica, et al.
Publicado: (2025)

A Survey on Federated Unlearning: Challenges and Opportunities
por: Jeong, Hyejun, et al.
Publicado: (2024)

Enhancing Security in Deep Reinforcement Learning: A Comprehensive Survey on Adversarial Attacks and Defenses
por: Yichao, Wu, et al.
Publicado: (2025)

AMIR-GRPO: Inducing Implicit Preference Signals into GRPO
por: Yari, Amir Hossein, et al.
Publicado: (2026)

A Practical Introduction to Deep Reinforcement Learning
por: Sun, Yinghan, et al.
Publicado: (2025)

Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities
por: Song, Yanjie, et al.
Publicado: (2023)

Handling Delay in Real-Time Reinforcement Learning
por: Anokhin, Ivan, et al.
Publicado: (2025)

Diffusion Models for Reinforcement Learning: A Survey
por: Zhu, Zhengbang, et al.
Publicado: (2023)

A Survey on Explainable Deep Reinforcement Learning
por: Cheng, Zelei, et al.
Publicado: (2025)

Reinforcement Learning for Generative AI: A Survey
por: Cao, Yuanjiang, et al.
Publicado: (2023)

Impartial Games: A Challenge for Reinforcement Learning
por: Zhou, Bei, et al.
Publicado: (2022)

Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
por: Yu, Dianzhi, et al.
Publicado: (2024)

A Comprehensive Survey on Evidential Deep Learning and Its Applications
por: Gao, Junyu, et al.
Publicado: (2024)

A Graph-Based Approach to Spectrum Demand Prediction Using Hierarchical Attention Networks
por: Alkadamani, Mohamad, et al.
Publicado: (2026)

A Survey of State Representation Learning for Deep Reinforcement Learning
por: Echchahed, Ayoub, et al.
Publicado: (2025)

A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders
por: Gonzales, Christophe, et al.
Publicado: (2024)

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

Exploring the impact of traffic signal control and connected and automated vehicles on intersections safety: A deep reinforcement learning approach
por: Karbasi, Amir Hossein, et al.
Publicado: (2024)

A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective
por: Xie, Xianghua, et al.
Publicado: (2023)