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...
贪婪算法(greedy algorithm)的思路非常直接:1、使用过去的数据去估计(estimate)一个模型(model); 2、选择能够optimize所估计模型的动作(action)。 那么在非贝叶斯的情形下,贪心算法不足之处是缺乏主动探索(active exploration)。 我们考虑贝叶斯情形下的Bernoulli Bandit的一个例子。在这个例子中,一共有3个action(arm)...
- 经典的强化学习算法(Reinforcement Learning(RL)),用于处理Exploration-Exploitation(EE) trade-off dilemma。 - 名字来源于casino中赌博机slot machine(or one armed bandit) 一个赌徒,要去摇老虎机,走进赌场一看,一排老虎机,外表一模一样,但是每个老虎机吐钱的概率可不一样,他不知道每个老虎机吐钱的概率分布是...
). Goal: Discuss on direction for UCB on action-values in RL, highlight some open questions and issues. Problem setting: Many model-free methods use uncertainty estimates: (1) Estimate uncertainty in Q(s, a), and (2) Reward bonuses or pseudo-counts. Let’s talk about (1) ...
This letter proposes a multi-armed bandit model-based vertical handoff approach (MABA). First, the vertical handoff problem is formulated as a multi-armed bandit problem. Then, the terminal services are divided into real-time services and non-real-time services, and their reward functions are ...
Research, Sunnyvale, CAAbstractWe provide a framework to exploit dependen-cies among arms in multi-armed bandit prob-lems, when the dependencies are in the formof a generative model on clusters of arms.We find an optimal MDP-based policy forthe discounted reward case, and also give an...
What is the multi-armed bandit problem? MAB is named after a thought experiment where a gambler has to choose among multiple slot machines with different payouts, and a gambler’s task is to maximize the amount of money he takes back home. Imagine for a moment that you’re the gambler. ...
2001AbstractInthemulti-armedbanditproblem,agamblermustdecidewhicharmofnon-identicalslotmachinestoplayinasequenceoftrialssoastomaximizehisreward.Thisclassicalproblemhasreceivedmuchattentionbecauseofthesimplemodelitprovidesofthetrade-offbetweenexploration(tryingouteacharmtofindthebestone)andexploitation(playingthearm...
RobustControloftheMulti-armedBanditProblemFelipeCaro∗AparupaDasGupta†UCLAAndersonSchoolofManagementSeptember9,2015ForthcominginAnnalsofOperationsResearchhttp://dx.doi/10.1007/s10479-015-1965-7AbstractWestudyarobustmodelofthemulti-armedbandit(MAB)probleminwhichthetransitionprobabilitiesareambiguousandbelongto...
The stochastic multi-armed bandit model is a simpleion that has proven useful in many different contexts in statistics and machine learning. Whereas the achievable limit in terms of regret minimization is now well known, our aim is to contribute to a better understanding of the performance in te...