Workshop / Overview
For the latest on the tutorial's schedule, setup hints, and frequent Q/A, Kindly read the tutorial's web page on: https://w12-Labs.github.io
The hands-on component starts with a code walk-through, to modify and experiment with simulator-based learning algorithms. Subsequently, the simulator-trained models are then deployed on 1:10 scale rovers for testing and evaluation. Furthermore, selected topics such as performance metrics, generalization, and architectural design/debugging concepts will be covered as time allows.
Participants are encouraged to form 2-4 person groups for an end of session competition.
Workshop / Outcome
Participants will be able to acquire sufficient understanding of the machine learning role within the presented classic control frameworks, and the associated real-world scenarios.
Workshop / Difficulty
Workshop / Prerequisites
- Fundamentals of Python
- Fundamentals of PyTorch
- Fundamentals of machine learning and/or control theory.
- A notebook with installed Python, PyTorch, and Gym.
Track / Co-organizers
A Conceptual Introduction to Reinforcement Learning
With Kevin Smeyers, Katrien Van Meulder & Bram Vandendriessche09:00-12:30 January 251ABC
Applied Machine Learning with R
With Dirk Wulff, Markus Steiner & Michael Schulte-Mecklenbeck09:00-17:00 January 25Foyer 6