(RL)approach is proposed for enabling mmWave concurrent transmissions by finding out beam directions that maximize the long-term average sum rates of the concurrent links.Specifically,the problem is formulated as a multiplayer multiarmed bandit(MAB),where mmWave APs act as the players aiming to ...
A contextual-bandit approach to personalized news article recommendation | Proceedings of the 19th international conference on World wide webdl.acm.org/doi/10.1145/1772690.1772758 论文背景: 已有的赌博机算法,例如E-Greedy、UCB、Thompson Smapling、朴素Bandit等,回报reward是算法自己内部决定的,而实际应用中...
啥是Multi-armed Bandit 想要知道啥是Multi-armed Bandit,首先要解释Single-armed Bandit,这里的Bandit,并不是传统意义上的强盗,而是指吃角子老虎机(Slot Machine)。按照英文直接翻译,这玩意儿叫“槽机”(这个翻译也是槽点满满),但是英语中称之为单臂强盗(Single-armed Bandit)是因为即使只有一个手臂(摇把),它也可以...
实际找到最佳手臂需要进行一些探索,否则我们可能会永远地拉下次优臂。 Epsilon Greedy Approach 一个潜在的解决方案可能是现在,然后我们可以探索新的行动,以便我们确保我们不会错过更好的选择。 使用epsilon概率,我们将选择随机动作(探索)并选择具有最大qt(a)且概率为1-epsilon的动作。 概率为1- epsilon - 我们选择具...
a lot of money on low-payoff machines. This is what can happen in an A/B test. The alternative is to focus on a few slots faster, continuously evaluate winnings, and maximize your investments over these slots for higher returns. This is what happens in the multi-armed bandit approach. ...
Automation for scale: If you have multiple components to continuously optimize, the multi-armed bandit approach gives you a framework to partially automate the optimization process for low-risk problems, which can be too costly to analyze individually.When...
Li, H., Shi, L., Zhong, X., Ji, Y., Zhang, S. (2023). Privacy-Aware Task Allocation with Service Differentiation for Mobile Edge Computing: Multi-armed Bandits Approach. In: Gao, F., Wu, J., Li, Y., Gao, H. (eds) Communications and Networking. ChinaCom 2022. Lecture Notes ...
Dynamic Pricing, Reinforcement Learning and Multi-Armed BanditIn the vast world of decision-making problems, one dilemma is particularly owned by Reinforcement Learning strategies: exploration versus exploitation. Imagine walking into a casino with rows of slot machines (also known as "one-armed band...
10.Decentralized Task Offloading in Edge Computing: A Multi-User Multi-Armed Bandit Approach11.Towards Revenue-Driven Multi-User Online Task Offloading in Edge Computing12.Dependent Task Offloading for Edge Computing based on Deep Reinforcement Learning13.Asynchronous Deep Reinforcement Learning for Data-...
Bandit algorithms sequentially accumulate data using adaptive sampling policies, offering flexibility for real-world applications. Paper Add Code Catoni Contextual Bandits are Robust to Heavy-tailed Rewards no code yet • 4 Feb 2025 When the variance of the reward at each round is known, we use...