Decision-Making for Autonomous Systems
Learn effective tactics for making key decisions when working with autonomous, self-driving vehicles.
About this course
In autonomous vehicles such as self-driving cars, we find a number of interesting and challenging decision-making problems. Starting from the autonomous driving of a single vehicle, to the coordination among multiple vehicles.
This course will teach you the fundamental mathematical model for many of these real-world problems. Key topics include Markov decision process, reinforcement learning and event-based methods as well as the modelling and solving of decision-making for autonomous systems.
This course is aimed at learners with a bachelor’s degree or engineers in the automotive industry who need to develop their knowledge in decision-making models for autonomous systems.
Enhance your decision-making skills in automotive engineering by learning from Chalmers, one of the top engineering schools that distinguished through its close collaboration with industry.
What you’ll learn
- Use Markov decision process (MDP) a mathematical framework for modellingdecision-making
- Understand and apply reinforcement learning and event-based methods
- Model and solve decision-making problems for autonomous systems
Language of instruction
The cause is taught in English
Lecturer
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