Generalized non-stationary bandits
Not on the map. Why?
Abstract (arXiv)
In this paper, we study a non-stationary stochastic bandit problem, which generalizes the switching bandit problem. On top of the switching bandit problem (Case a), we are interested in three concrete examples: (b) the means of the arms are local polynomials, (c) the means of the arms are locally smooth, and (d) the gaps of the arms have a bounded number of inflexion points and where the highest arm mean cannot vary too much in a short range. These three settings are very different, but have in common the following: (i) the number of similarly-sized level sets of the logarithm of the gaps can be controlled, and (ii) the highest mean has a limited number of abrupt changes, and otherwise has limited variations. We propose a single algorithm in this general setting, that in particular solves in an efficient and unified way the four problems (a)-(d) mentioned.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 11 of its 31 references that are in the map. First posted on arXiv 1 Feb 2021.
Builds on
11 of 31 references.
References · 11
- 2018Learning to Optimize under Non-Stationaritycited by 85
- 2019Weighted Linear Bandits for Non-Stationary Environmentscited by 84
- 2019A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-freecited by 71
- 2018What Doubling Tricks Can and Can't Do for Multi-Armed Banditscited by 69
- 2017Rotting Banditscited by 57
- 2018Nearly Optimal Adaptive Procedure with Change Detection for Piecewise-Stationary Banditcited by 49
- 2017A Change-Detection based Framework for Piecewise-stationary Multi-Armed Bandit Problemcited by 48
- 2014Unimodal Bandits: Regret Lower Bounds and Optimal Algorithmscited by 36
- 2017Tracking the Best Expert in Non-stationary Stochastic Environmentscited by 35
- 2015Multi-armed Bandit Problem with Known Trendcited by 17
- 2016On the Whittle Index for Restless Multi-armed Hidden Markov Banditscited by 12
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3; 2025: 1; 2026: 1.
8 papers.
- 2021Tracking Most Significant Arm Switches in Banditscited by 27
- 2023Smooth Non-Stationary Banditscited by 13
- 2022Testing Stationarity and Change Point Detection in Reinforcement Learningcited by 12
- 2024Adaptive Smooth Non-Stationary Banditscited by 4
- 2025Tracking Most Significant Shifts in Infinite-Armed Banditscited by 1
- 2024Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rottingcited by 0
- 2024Diminishing Exploration: A Minimalist Approach to Piecewise Stationary Multi-Armed Banditscited by 0
- 2026A Modularized Framework for Piecewise-Stationary Restless Banditscited by 0
- 2026A Modularized Framework for Piecewise-Stationary Restless Bandits11 Apr 2026
- 2025Tracking Most Significant Shifts in Infinite-Armed Bandits31 Jan 2025
- 2024Diminishing Exploration: A Minimalist Approach to Piecewise Stationary Multi-Armed Bandits8 Oct 2024
- 2024Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting9 Sep 2024
- 2024Adaptive Smooth Non-Stationary Bandits11 Jul 2024
- 2023Smooth Non-Stationary Bandits29 Jan 2023
- 2022Testing Stationarity and Change Point Detection in Reinforcement Learning3 Mar 2022
- 2021Tracking Most Significant Arm Switches in Bandits27 Dec 2021