多臂老虎机问题(Multi-Armed Bandit Problem)源自赌博机(老虎机)的概念,用于描述一个探索与开发(exploration-exploitation)的平衡问题。想象你站在一排老虎机前,每台老虎机有不同的概率分布,代表你每次拉杆可能赢得的奖金。你的目标是通过尽量少的尝试找出哪台老虎机能让你赚最多的钱。 详细回答 多臂老虎机问题在...
问题定义 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...
Years and Authors of Summarized Original Work 2002; Auer, Cesa-Bianchi, Freund, Schapire 2002; Auer, Cesa-Bianchi, Fischer Problem Definition A multi-armed bandit is a sequential decision problem defined on a set of actions. At each time step, the decision maker selects an action from the ...
1、问题介绍:k-armed Bandit Problem Multi-armed bandit原本是从赌场中的多臂老虎机的场景中提取出来的数学模型,其中 arm 指的是老虎机(slot machine)的拉杆,bandit 是多个拉杆的集合,bandit=arm1,arm2,……,armkbandit=arm1,arm2,……,armk。每个 bandit setting 对应一个回报函数(reward function),现在需要...
). 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) ...
Keywords:multiarmedbandit;indexpolicies;Bellmanequation;robustMarkovdecisionpro- cesses;uncertaintransitionmatrix;projectselection. 1.Introduction TheclassicalMulti-armedBandit(MAB)problemcanbereadilyformulatedasaMarkovdecision process(MDP).AtraditionalassumptionfortheMDPformulationisthatthestatetransition probabilitiesare...
Chapter 2 Multi-armed Bandits 查看原文 RL an introduction学习笔记(1):Muti-arm Bandits Greedy算法1.从问题入手: 1.1问题描述:Muti-armBanditsMuti-armedBandits(多臂老虎机)问题,也叫K-armedBanditProblem... value) q_estimate是一个1*10的列表,记录agent对每一个老虎机价值的估计值 act()方法是依据算法(...
There are many different solutions that computer scientists have developed to tackle the multi-armed bandit problem. Below is a list of some of the most commonly used multi-armed bandit solutions:Epsilon-greedy This is an algorithm for continuously balancing exploration with exploitation. (In ‘...
总结: Multi-armed bandit problem(又称k-armed bandit problem)并非完全的reinforcement learning,而只是其简化版本。 所以该书将bandit问题作为引子,引出reinforcement learning的问题。reinforcement learning中的一些概念都是其中的一些概念扩展而来的。
第二章 Multi-armed Bandits读书笔记 目录 Part I:Tabular Solution Methods Chapter 2 Multi_armed Bandits 2.1 k臂赌博机问题(A k-armed Bandit Problem) 2.2 值函数方法(action——value method) 2.3 10臂测试(The 10-armed Testbed) 2.4增量实现(Incremental Implementation)...