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Autonomous Big Data Optimization: Multi-Agent Reinforcement Learning to Achieve Self-Tuning Apache Spark
This article introduces a reinforcement learning (RL) approach grounded in Apache Spark that enables distributed computing systems to learn optimal configurations autonomously, much like an apprentice engineer who learns by doing. The author also implements a lightweight agent as a driver-side component that uses RL to choose configuration settings before a job runs.
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Reinforcement Machine Learning for Effective Clinical Trials
In this article, author Dattaraj Jagdish Rao explores the reinforcement machine learning technique called Multi-armed Bandits and discusses how it can be applied to areas like website design and clinical trials.