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Deep reinforcement learning’s killer app: Intelligent control in real-world systems

This will be presented in English.

Mark Hammond (Microsoft)
13:1013:50 Friday, April 13, 2018
Secondary topics:  制造业与工业自动化 (Manufacturing and Industrial Automation), 增强学习(Reinforcement Learning)

必要预备知识 (Prerequisite Knowledge)

General experience with programming

您将学到什么 (What you'll learn)

Explore case studies to understand the best use cases and business impact of applied deep reinforcement learning and see step-by-step how to build, train, and deploy models onto real-world systems

描述 (Description)


Reinforcement learning is a powerful machine learning technique for solving problems in dynamic and adaptive environments. Combined with a simulation or digital twin, reinforcement learning can train models to automate or optimize the efficiency of industrial systems and processes such as robotics, manufacturing, energy, and supply chain.

But what comes after the simulation? Mark Hammond dives into two real-world case studies to show how deep reinforcement learning successfully automated the machine tuning of a Fortune 500 manufacturing system and optimized energy efficiency of a large-scale HVAC system. Mark details the end-to-end process of building, training, and deploying models and examines the business impact of each application.


但在模拟完后又要做什么?Mark Hammond将会详细介绍两个真实世界的案例,来展示增强学习是如何成功地自动化了一个财富500强制造业企业的机器调优,以及如何优化了一个大型空调企业的系统的能效。Mark将会详细介绍从构建、训练、部署模型到分析应用的业务影响的全过程。

Photo of Mark Hammond

Mark Hammond


Mark Hammond is cofounder and CEO at Bonsai. Mark has a deep passion for understanding how the mind works and has been thinking about AI throughout his career. He has held positions at Microsoft and numerous startups and in academia, including turns at Numenta and in the Yale Neuroscience Department. He holds a degree in computation and neural systems from Caltech.