Autonomous and Adaptive Systems

Course page here.

Preface

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.

Strong focus on the state-of-the-art (and what’s next): read papers from leading AI/ML conferences (but also classics from the ML field), try software, etc.

Topics of the Module

Interesting News and Readings

• The Dartmouth Summer Research Project on Artificial Intelligence: Solomonoff (06 May 2023).

• Andrew Barto and Richard Sutton Recognized as Pioneers of Reinforcement Learning: Ormond (2024).

• To catch up with Probability and Computing: Mitzenmacher (2017).

Papers’ sources

• Google Scholar (scholar.google.com)

Mitzenmacher, Michael. 2017. Probability and Computing. Second edition. Cambridge University Press. https://www.cambridge.org/jp/universitypress/subjects/computer-science/algorithmics-complexity-computer-algebra-and-computational-g/probability-and-computing-randomization-and-probabilistic-techniques-algorithms-and-data-analysis-2nd-edition.

Ormond, Jim. 2024. “2024 Turing Award.” ACM. https://awards.acm.org/about/2024-turing.

Solomonoff, Grace. 06 May 2023. “The Meeting of the Minds That Launched AI.” IEEE Spectrum. https://spectrum.ieee.org/dartmouth-ai-workshop.