fortiss wants to make the topic of artificial intelligence (AI) tangible for companies in this sector and has developed the AI tutorial Intelligent Control as part of the Mittelstand-Digital Zentrum Augsburg.

Learn how you can optimally control your processes and achieve high-quality results. The decisive factor here is adapting the relevant parameters. In this tutorial, you will learn how to do this with the help of reinforcement learning. The method is part of machine learning.

The intelligent control of an elevator serves as a prototypical example here. An agent should independently learn how the elevator moves efficiently between floors in order to minimize the total waiting time of all passengers. As a user, all you have to do is define a reward signal that tells the agent whether it is moving in the right direction.

It is helpful if you have already come into contact with the Python programming language, but it is not absolutely necessary. Otherwise, technical computer skills (e.g. installation of software) that go beyond pure Office knowledge are sufficient.

Contents

• Introduction to reinforcement learning (RL)
• Exemplary application of reinforcement learning in industry through the intelligent control of an elevator
• Creation of an RL code framework for the implementation of a self-learning agent

Benefits for users

• They learn how to use reinforcement learning and can contribute to improving the efficiency and quality of process control in the production environment
• You only need a reduced amount of expert and domain knowledge, as RL can partly learn from data itself
• Reinforcement learning enables more robust control, as an RL agent can adapt to a certain degree to unforeseen events over time

The digital learning offer gives companies the opportunity to train themselves independently and get to know different AI areas. Thanks to the online format and a detailed explanation, the online tutorial can be worked through at your own pace.

AI tutorial intelligent control

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