2015
NIPS
NeurIPS 2015
When are Kalman-Filter Restless Bandits Indexable?
Abstract
We study the restless bandit associated with an extremely simple scalar Kalman filter model in discrete time. Under certain assumptions, we prove that the problem is {\it indexable} in the sense that the {\it Whittle index} is a non-decreasing function of the relevant belief state. In spite of the long history of this problem, this appears to be the first such proof. We use results about {\it Schur-convexity} and {\it mechanical words}, which are particularbinary strings intimately related to {\it palindromes}.
❓
The Questioner
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
🧭
Keyword Pioneer
— whittle index
🐣
Hot Topic Early Bird
— stochastic process
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio