[TMP-038] Educational module Human-Interactive Robot Learning (HIRL)
The project focuses on creating robots that learn from human interaction and can adapt to different teaching styles. The research also explores decentralized learning and process model discovery from data.
Human-Interactive Robot Learning (HIRL) is a robotics field focused on creating robots that learn from and interact with humans. This module covers the fundamental principles and techniques of HIRL. This interdisciplinary module will encourage graduate students (Master/PhD level) to connect different bodies of knowledge within the broad field of Artificial Intelligence, with insights from Robotics, Machine Learning, Human Modelling, and Design and Ethics. The module is meant for Master’s and PhD students in STEM, such as Computer Science, Artificial Intelligence, and Cognitive Science. This work will extend the tutorial presented in the context of the International Conference on Algorithms, Computing, and Artificial Intelligence (ACAI 2021) and will be shared with the Artificial Intelligence Doctoral Academy (AIDA). Moreover, the proposed lectures and assignments will be used as teaching material at Sorbonne University, and Vrije Universiteit Amsterdam. We plan to design a collection of approximately 12 1.5-hour lectures, 5 assignments, and a list of recommended readings, organized along relevant topics surrounding HIRL. Each lecture will cover an algorithmic component and a practical example of integrating it into an interactive system. Assignments will involve replicating existing algorithms and allowing students to create their own alternative solutions.
Partners:
- ISIR, Sorbonne University, Mohamed Chetouani, Silvia Tulli
- Vrije Universiteit Amsterdam, Kim Baraka