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 exploitation dilemma,他的regret至少是以动作次数的对数增长的,但是这个结论只是渐进性的,不够具体。作者就分析了四个具体算法的finite-time下的性质。 分析的第一个算法是经典的UC...
文档标签: Robust Control of the Multi-Armed Bandit Problem多武装强盗问题的鲁棒控制 系统标签: robust bandit problem armed 鲁棒 强盗 RobustControloftheMulti-armedBanditProblemFelipeCaro∗AparupaDasGupta†UCLAAndersonSchoolofManagementSeptember9,2015ForthcominginAnnalsofOperationsResearchhttp://dx.doi/10.1007...
After observing the states of each project, one project has to be selected to work on for the next period. If project k is selected and the state of the project is i , the we receive an expected reward r k (i) and the next state of project k becomes j with prohability p k (i...
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 ...
Leslie Pack Kaelbling Abstract The stochastic multi-armed bandit problem is an important model for studying the exploration- exploitation tradeoff in reinforcement learning. Although many algorithms for the problem are well-understood theoretically, empirical confirmation of their effectiveness is generally sca...
【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
2012. Analysis of Thompson Sampling for the Multi-armed Bandit Problem.. In COLT. 39-1.S. Agrawal and N. Goyal, "Analysis of thompson sampling for the multi-armed bandit problem," in COLT 2012, 2012.Agrawal, S., N. Goyal. 2012. Analysis of Thompson sampling for the multi-armed ...
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....
We consider a multi-armed bandit problem in a setting where each arm produces a noisy reward realization which depends on an observable random covariate. As opposed to the traditional static multi-armed bandit problem, this setting allows for dynamically
The following coins problem is a version of a multi-armed bandit problem where one has to select from among a set of objects, say classifiers, after an experimentation phase that is constrained by a time or cost budget. The question is how to spend the budget. The problem involves pure ...