Decision-Making for Autonomous Systems
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.
Who should attend?
Course delivery details
This course is offered through Chalmers University of Technology, a partner institute of EdX.
10-20 hours per week
- Verified Track -$249
- Audit Track - Free
Certification / Credits
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
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