Autonomous and Adaptive Systems 2023-24
Overview
This course will provide the students with a solid understanding of the state of the art and the key conceptual and practical aspects of the design, implementation and evaluation of intelligent machines and autonomous systems that learn by interacting with their environment. The course also takes into consideration ethical, societal and philosophical aspects related to these technologies.
Link to official course page containing syllabus and textbooks
Teaching Team
Mirco Musolesi (Instructor)
Giorgio Franceschelli (Teaching Assistant)
Notices
The enrolment for the exam sessions in June and July 2024 is now open.
Mailing List of the Course
Please join the mailing list of the course by signing up through this form.
The instructor will use this mailing list exclusively to send all the information regarding the module, including organisation of the lectures, additional material, exams, etc. Please sign-up using your institutional address.
Slides of the Lectures
Intelligent Agents and Machines
Introduction to Reinforcement Learning
Deep Learning and Neural Architectures - First Part
Deep Learning and Neural Architectures - Second Part
Deep Learning and Neural Architectures - Third Part
Slides of the Practicals
Advanced TensorFlow for Reinforcement Learning
Slides of the Tutorials
Slides about Project Guidelines
Notebooks
Last updated: 17 May 2024.