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Reading group on cognitive abilities in artificial systems

8.3222

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Beschreibung

Content and goal:
In this course, you will explore research on computational approaches to understanding cognitive abilities. We will study systems and algorithms such as ACT-R, AlphaStar, GPT, MAML, NEAT, and Spaun. Every week, we will discuss classic and newly emerging research articles the instructors and the group decided on during the course. Each student, or group of students, depending on the number of students enrolled, will be required to prepare and present at least one paper, to guide the group through it and to lead the in-depth discussion. By the end of the course, you will have a wide understanding of the common conceptualizations and trends in this research direction. You will be better at parsing papers - getting to the central messages quickly and assessing the validity of the claims being made.

Target audience:
Master students who have at least completed an introductory course in deep learning. Highly motivated bachelors students are welcome. Bear in mind that the course content will be complex.

Number of participants:
The number of participants in this course is limited. Suppose more students than the maximum number apply. In that case, we will choose a subgroup based on fulfillment of course criteria (see "target audience" above), as well as experience and, likely, motivation letters. The exact procedure will be communicated in the first session once we can tell how many students are actively taking part.

Grading:
The course will be completed with a written report, to be handed in by each student, in which you will be asked to answer a guiding question or review a common theme among the papers covered. The course grade will be partly based on the weekly presentations and the report.

Weitere Angaben

Ort: 50/E07
Zeiten: Do. 16:00 - 18:00 (wöchentlich)
Erster Termin: Donnerstag, 07.11.2024 16:00 - 18:00, Ort: 50/E07
Veranstaltungsart: Seminar (Offizielle Lehrveranstaltungen)