School of EngineeringOpen OpportunitiesThe thesis will address methodological gaps to achieve effective and safety-critical RL-based optimal control.
The project will include:
1. Reviewing existing RL approaches for continuous state-action spaces.
2. Developing ideas to tackle the challenges of optimal control systems with stability guarantees.
3. Python implementation of these algorithms in simulated physical environments, with varying degrees of complexity based on the student's computer science background.
This project offers a unique opportunity to enhance your knowledge and skills in machine learning, control theory, and optimization. - Engineering and Technology, Information, Computing and Communication Sciences
- Master Thesis
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