Teachers
Alberto Testolin
Dipartimento di Psicologia Generale, Università degli Studi di Padova,
alberto.testolin@unipd.it
INFO-01/A

Aim
The aim of the course is to introduce the student to the leading frameworks to understand human cognition from a computational perspective. This is relevant both for understanding how the mind works as well as for the design of advanced artificial intelligence systems. The course will introduce the student to philosophical debates in the study of the mind/brain problem and then focus on the connectionist approach for studying the neurocomputational bases of cognition. Theoretical discussion will be complemented by case studies from the cognitive modeling literature and from the recent progresses in AI research.

Syllabus
- What is cognitive modeling and how does it relate to AI research?
- Levels of analysis in cognitive modeling.
- Philosophical perspectives on the nature of human thinking.
- Symbolic vs. emergentist models.
- Feed-forward vs. generative neural networks.
- Large Language Models and the quest for “understanding”.
- Cognitive benchmarks for evaluating AI systems.
- Situated agents and case studies in cognitive modeling.
- What is missing? A comparison between artificial and biological cognition.

Course requirements
The student is expected to have basic knowledge of probability theory and machine learning.

Examination modality
None

Course material, enrollment and last-minute notifications
Made available by the teacher at this Moodle address

Schedule and Location

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