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Decision-Making for Autonomous Systems

Emerging Automotive Technologies,

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

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Rating Not enough ratings
Length 7 weeks
Effort 7 weeks, 10–20 hours per week
Starts On Demand (Start anytime)
Cost $249
From Chalmers University of Technology, ChalmersX via edX
Instructors Samuel Jia Qing-Shan, Jonas Sjöberg
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science Mathematics
Tags Computer Science Data Analysis & Statistics Math Engineering

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Rating Not enough ratings
Length 7 weeks
Effort 7 weeks, 10–20 hours per week
Starts On Demand (Start anytime)
Cost $249
From Chalmers University of Technology, ChalmersX via edX
Instructors Samuel Jia Qing-Shan, Jonas Sjöberg
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science Mathematics
Tags Computer Science Data Analysis & Statistics Math Engineering

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