Copertina

Contextual Restless Multi-Armed Bandits with Application to Demand Response Decision-Making

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Xin, Hou, I-Hong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

IRL for Restless Multi-Armed Bandits with Applications in Maternal and Child Health
di: Jain, Gauri, et al.
Pubblicazione: (2024)

Global Rewards in Restless Multi-Armed Bandits
di: Raman, Naveen, et al.
Pubblicazione: (2024)

Restless Multi-Process Multi-Armed Bandits with Applications to Self-Driving Microscopies
di: Peris, Jaume Anguera, et al.
Pubblicazione: (2025)

A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health
di: Behari, Nikhil, et al.
Pubblicazione: (2024)

Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback
di: Xiong, Guojun, et al.
Pubblicazione: (2024)

Decisions and Deployment: The Five-Year SAHELI Project (2020-2025) on Restless Multi-Armed Bandits for Improving Maternal and Child Health
di: Verma, Shresth, et al.
Pubblicazione: (2026)

Multi-Armed Bandits-Based Optimization of Decision Trees
di: Shanto, Hasibul Karim, et al.
Pubblicazione: (2025)

CAREForMe: Contextual Multi-Armed Bandit Recommendation Framework for Mental Health
di: Yu, Sheng, et al.
Pubblicazione: (2024)

Flickering Multi-Armed Bandits
di: Chakraborty, Sourav, et al.
Pubblicazione: (2026)

Networked Restless Multi-Arm Bandits with Reinforcement Learning
di: Zhang, Hanmo, et al.
Pubblicazione: (2025)

Context Attribution with Multi-Armed Bandit Optimization
di: Pan, Deng, et al.
Pubblicazione: (2025)

On the Benefits of Free Exploration for Regret Minimization in Multi-Armed Bandits
di: Hou, Yunlong, et al.
Pubblicazione: (2026)

Introduction to Multi-Armed Bandits
di: Slivkins, Aleksandrs
Pubblicazione: (2019)

Multi-Armed Bandits With Best-Action Queries
di: Bacchiocchi, Francesco, et al.
Pubblicazione: (2026)

Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning
di: Li, Sijia, et al.
Pubblicazione: (2026)

Survey: Multi-Armed Bandits Meet Large Language Models
di: Bouneffouf, Djallel, et al.
Pubblicazione: (2025)

Fair Algorithms with Probing for Multi-Agent Multi-Armed Bandits
di: Xu, Tianyi, et al.
Pubblicazione: (2025)

Large Language Model-Enhanced Multi-Armed Bandits
di: Sun, Jiahang, et al.
Pubblicazione: (2025)

Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization
di: Zhao, Yunfan, et al.
Pubblicazione: (2023)

Contextual Bandit with Herding Effects: Algorithms and Recommendation Applications
di: Xu, Luyue, et al.
Pubblicazione: (2024)

Federated Combinatorial Multi-Agent Multi-Armed Bandits
di: Fourati, Fares, et al.
Pubblicazione: (2024)

Mobility-Aware Federated Learning: Multi-Armed Bandit Based Selection in Vehicular Network
di: Tu, Haoyu, et al.
Pubblicazione: (2024)

Thresholding Data Shapley for Data Cleansing Using Multi-Armed Bandits
di: Namba, Hiroyuki, et al.
Pubblicazione: (2024)

Lagrangian Index Policy for Restless Bandits with Average Reward
di: Avrachenkov, Konstantin, et al.
Pubblicazione: (2024)

Near-Optimal Regret for KL-Regularized Multi-Armed Bandits
di: Ji, Kaixuan, et al.
Pubblicazione: (2026)

Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi
di: Wilhelmi, Francesc, et al.
Pubblicazione: (2024)

On the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization
di: Ji, Kaixuan, et al.
Pubblicazione: (2026)

Annealed Softmax Greedy in Many-Armed Bayesian Bandits
di: Overman, William, et al.
Pubblicazione: (2026)

Balancing Act: Prioritization Strategies for LLM-Designed Restless Bandit Rewards
di: Verma, Shresth, et al.
Pubblicazione: (2024)

Online Prompt Pricing based on Combinatorial Multi-Armed Bandit and Hierarchical Stackelberg Game
di: Li, Meiling, et al.
Pubblicazione: (2024)

ParBalans: Parallel Multi-Armed Bandits-based Adaptive Large Neighborhood Search
di: Yilmaz, Alican, et al.
Pubblicazione: (2025)

Optimizing Vital Sign Monitoring in Resource-Constrained Maternal Care: An RL-Based Restless Bandit Approach
di: Boehmer, Niclas, et al.
Pubblicazione: (2024)

Adaptive Budgeted Multi-Armed Bandits for IoT with Dynamic Resource Constraints
di: Vaishnav, Shubham, et al.
Pubblicazione: (2025)

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization
di: Duan, Shaohua, et al.
Pubblicazione: (2025)

Deep Index Policy for Multi-Resource Restless Matching Bandit and Its Application in Multi-Channel Scheduling
di: Zamir, Nida, et al.
Pubblicazione: (2024)

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users
di: Yang, Hantao, et al.
Pubblicazione: (2024)

STRIDE: Strategic Iterative Decision-Making for Retrieval-Augmented Multi-Hop Question Answering
di: Chen, Wei, et al.
Pubblicazione: (2026)

Optimizing Urban Service Allocation with Time-Constrained Restless Bandits
di: Mao, Yi, et al.
Pubblicazione: (2025)

Demystifying Design Choices of Reinforcement Fine-tuning: A Batched Contextual Bandit Learning Perspective
di: Xie, Hong, et al.
Pubblicazione: (2026)

Tree Ensembles for Contextual Bandits
di: Nilsson, Hannes, et al.
Pubblicazione: (2024)