**发表时间:**2002(Machine Learning, 47, 235–256, 2002) **文章要点:**这篇文章主要是分析了针对Multiarmed Bandit Problem的几个经典算法的收敛性。我们知道这类问题主要就是在解决exploration versus exploit
Test Run - The Multi-Armed Bandit Problem Windows PowerShell - Writing Windows Services in PowerShell The Working Programmer - How To Be MEAN: Getting the Edge(.js) Visual Studio - Nurturing Lean UX Practices Don't Get Me Started - Left Brains for the Right Stuff ...
RobustControloftheMulti-armedBanditProblem FelipeCaro ∗ AparupaDasGupta † UCLAAndersonSchoolofManagement September9,2015 ForthcominginAnnalsofOperationsResearch http://dx.doi/10.1007/s10479-015-1965-7 Abstract Westudyarobustmodelofthemulti-armedbandit(MAB)probleminwhichthetransition probabilitiesare...
Robust Control of the Multi-armed Bandit Problem Felipe Caro Aparupa Das Gupta UCLA Anderson School of Management September 9, 2015 Forthcoming in Annals of Operations Research http://dx.doi.org/10.1007/s10479-015-1965-7 Abstract We study a robust model of the multi-armed bandit (MAB) ...
【多臂老虎机问题及其解法】《The Multi-Armed Bandit Problem and Its Solutions》by Lilian Weng http://t.cn/E5PVtrX GitHub:http://t.cn/EilVLTF
The multi-armed bandit problem is a classic reinforcement learning example where we are given a slot machine with n arms (bandits) with each arm having its own rigged probability distribution of…
that is the loss due to the fact that the globally optimal policy is not followed all the times. One of the simplest examples of the exploration/exploitation dilemma is the multi-armed bandit problem. Lai and Robbins were the first ones to show that the regret for this problem has to grow...
In this paper, we propose a set of allocation strategies to deal with the multi-armed bandit problem, the possibilistic reward (PR) methods. First, we use possibilistic reward distributions to model the uncertainty about the expected rewards from the arm, derived from a set of infinite ...
The Multi-Armed Bandit ProblemSun, 01 May 2016 10:00:00 GMTJames McCaffrey provides an implementation of the multi-armed bandit problem, which is not only interesting in its own right, it also serves as a good introduction to an active area of economics and machine learning research....
Algorithms for the multi-armed bandit problem work. Evaluation done in this context is often performed on a small number of bandit prob- lem instances (for example, on bandits with small numbers of arms) that may not generalize to other settings. Moreover, different authors evaluate their algor...