edX Decision-Making for Autonomous Systems

Overview
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 modelling decision-making
• Understand and apply reinforcement learning and event-based methods
• Model and solve decision-making problems for autonomous systems

Taught by
Samuel Jia Qing-Shan