Autonomous and Adaptive Systems 2025-26
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
27 March 2026 The lectures will start on 27 February 2026. Please enrol in the mailing list below.
Mailing List
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Slides of the Lectures
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
Policy Gradient Methods - First Part
Slides of the Practicals
Advanced TensorFlow for Reinforcement Learning
Last updated: 6 April 2026.