Air Path Control with Multi agent Reinforcement Learning
AVL
Graz, AT
vor 4 Tg.

AVL is the world’s largest independent company for development, simulation and testing in the automotive industry, and in other sectors.

As a global technology leader, AVL provides concepts, solutions and methodologies in the fields of e-mobility, ADAS and autonomous driving, vehicle integration, digitalization, virtualization, Big Data, and much more.

We offer a thesis with the topic of

A combination of multiple autonomous agents trained in a common environment with Multi-agent reinforcement learning (MARL) shall be applied to improve the control strategy of an air path control system for diesel engines.

The following tasks shall be performed during this thesis :

TASK :

  • Literature review
  • Environment Setup for MARL (supported by AVL)
  • Applying MARL algorithms to create the model
  • Model evaluation with different algorithms
  • Integration of the machine learning model with the other SW modules
  • Validation with test cases provided by AVL
  • REQUIREMENTS :

  • Strong programming skills in Python
  • Being familiar with Python libraries and ML frameworks, such as Numpy , Pandas, Tensorflow , Keras ,
  • Control theory basics
  • PREFERRED FIELD OF STUDY :

  • Telematics / Informatics
  • Electrical / Electronic Engineering
  • The successful completion of the thesis is remunerated with a one-time fee of EUR €2,600.00 before tax.

    According to the Austrian Employment of Foreign Nationals Act it is unfortunately not possible to assign graduate work to third-country citizens (Non-EU citizens) who study at a university abroad

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