多臂赌博机问题(multi-armed bandit) 多臂赌博机是一个经典的问题。通常用来作为RL的入门级demo。所谓的k-armed bandit指的是这样一个任务:在你面前有一个类似老虎机的k个手柄的游戏机,每次选择并拉一个手柄,就会得到一个数值(可能是奖金金额),这个金额是一个随机数,它的分布对于每个手柄都是不同的,而你的任...
Federated multi-armed bandits(FMAB)是新的bandit范式,主要灵感来源于cognitive radio 和recommender systems的实际应用场景。这篇论文提出了一个通用型FMAB框架,并研究了该框架下的两种模型。 首先研究了近似模型,在该近似模型中,不同的local model都是global model 的服从于一个未知分布的随机实现。在这个近似模型中,...
- MAB问题也在stochastic scheduling领域范畴中。Stochastic scheduling problems can be classified into three broad types: problems concerningthe scheduling of a batch of stochastic jobs,multi-armed banditproblems, andproblems concerning the scheduling of queueing systems. 基本问题 1. 有K台machine,每次选取其...
- MAB问题也在 stochastic scheduling 领域范畴中。Stochastic scheduling problems can be classified into three broad types: problems concerning the scheduling of a batch of stochastic jobs , multi-armed bandit problems , and problems concerning the scheduling of queueing systems. 1. 有K台machine,每次...
Q: Why is RL from the contextual bandit setting? A1: Temporal connections. A2: Bootstrapping – do not get a sample of the target, especially since the policy is changing.Idea for UCB in RL: UCB for a fixed policy. Apply our usual concentration inequalities to obtain the ...
2014. Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species risk, Journal of Environmental Economics and Management, 68, 226-242.Springborn MR. 2014. Risk aversion and adaptive management: Insights from a multi-armed bandit model of invasive species ...
We model how a judge schedules cases as a multiarmed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level...
Multiarmed bandit problemstochastic schedulingMarkov decision processesoptimal stoppingsequential methodsThis paper considers the multiarmed bandit problem and ... Weber,Richard - 《Annals of Applied Probability》 被引量: 414发表: 1992年 Hidden Markov model multiarm bandits: a methodology for beam schedul...
Bourne强化学习笔记3:在简单的Bandit问题中抓住强化学习的本质 .Nonstationary,即概率分布不确定。 对于Stationary情况,在此举一个10-armedbandit问题,来测试单纯的greedy学习策略和ε-greedy学习策略的学习...Bandit,即在该问题中,只有一个state,经历完该state,该问题就结束了。k-armedBandit则是在该state中有k个选择...
赌场的老虎机有一个绰号叫单臂强盗(single-armed bandit),因为它即使只有一只胳膊,也会把你的钱拿走。而多臂老虎机(或多臂强盗)就从这个绰号引申而来。假设你进入一个赌场,面对一排老虎机(所以有多个臂),由于不同老虎机的期望收益和期望损失不同,你采取什么老虎机选择策略来保证你的总收益最高呢?这就是经典的...