Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
When are Kalman-Filter Restless Bandits Indexable?
Authors: Christopher R. Dance, Tomi Silander
NeurIPS 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Under certain assumptions, we prove that the problem is indexable in the sense that the 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 ο¬rst such proof. |
| Researcher Affiliation | Industry | Christopher Dance and Tomi Silander Xerox Research Centre Europe 6 chemin de Maupertuis, Meylan, Is ere, France EMAIL |
| Pseudocode | No | The paper contains mathematical definitions and proofs but no structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not mention any release of open-source code. |
| Open Datasets | No | The paper is theoretical and does not use or refer to any empirical datasets, training data, or their public availability. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments or dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not mention any hardware specifications used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not list any software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |