Document detail
ID

oai:arXiv.org:2410.09781

Topic
Computer Science - Machine Learnin... Computer Science - Information Ret... Statistics - Machine Learning
Author
Guo, Zhanqiu Wang, Wayne
Category

Computer Science

Year

2024

listing date

10/16/2024

Keywords
learning model neurwin
Metrics

Abstract

This study introduces ContextWIN, a novel architecture that extends the Neural Whittle Index Network (NeurWIN) model to address Restless Multi-Armed Bandit (RMAB) problems with a context-aware approach.

By integrating a mixture of experts within a reinforcement learning framework, ContextWIN adeptly utilizes contextual information to inform decision-making in dynamic environments, particularly in recommendation systems.

A key innovation is the model's ability to assign context-specific weights to a subset of NeurWIN networks, thus enhancing the efficiency and accuracy of the Whittle index computation for each arm.

The paper presents a thorough exploration of ContextWIN, from its conceptual foundation to its implementation and potential applications.

We delve into the complexities of RMABs and the significance of incorporating context, highlighting how ContextWIN effectively harnesses these elements.

The convergence of both the NeurWIN and ContextWIN models is rigorously proven, ensuring theoretical robustness.

This work lays the groundwork for future advancements in applying contextual information to complex decision-making scenarios, recognizing the need for comprehensive dataset exploration and environment development for full potential realization.

Guo, Zhanqiu,Wang, Wayne, 2024, ContextWIN: Whittle Index Based Mixture-of-Experts Neural Model For Restless Bandits Via Deep RL

Document

Open

Share

Source

Articles recommended by ES/IODE AI

Skin cancer prevention behaviors, beliefs, distress, and worry among hispanics in Florida and Puerto Rico
skin cancer hispanic/latino prevention behaviors protection motivation theory florida puerto rico variables rico psychosocial behavior response efficacy levels skin cancer participants prevention behaviors spanish-preferring tampeños puerto hispanics