AI-1 Systems Project (AI1SysProj)10 ECTS
(englische Bezeichnung: AI-1 Systems Project)

Lectures:

• • AI-1 Systems Project
    (Projektseminar, 4 SWS, Michael Kohlhase et al., Tue, 14:15 - 16:00, Zoom-Meeting)

Empfohlene Voraussetzungen:

Strong programming skills in any programming language.

Inhalt:

This project complements the symbolic AI methods covered in the AI-1 Lecture with practical experience in implementing the algorithms or applying existing state-of-the-art libraries and systems. Practical areas of covered in this project include

• Logic Programming

• Rational Agents

• Search (classical/adversarial)

• Constraint Satisfaction/Propagation

• Propositional/First-Order Reasoning

• Knowledge Representation

• Planning

Project participants will work on multiple concrete problems/applications in small project teams. The results will be

• evaluated using benchmark/problems and/or competitions between project teams.

• documented in (short) project reports and be presented to the group.

Lernziele und Kompetenzen:

Students will

• develop and implement algorithms or apply existing systems/libraries to multiple symbolic AI Problems,

• acquire hands-on experience in an established research field,

• learn best practices in software development and documentation,

• gain first experience in academic writing.

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:
Das Modul ist im Kontext der folgenden Studienfächer/Vertiefungsrichtungen verwendbar:

1. Artificial Intelligence (Master of Science)
   (Po-Vers. 2021s | TechFak | Artificial Intelligence (Master of Science) | Gesamtkonto | Projekt I und II | Symbolic Artificial Intelligence | AI-1 Systems Project)
2. Informatik (Master of Science)
   (Po-Vers. 2010 | TechFak | Informatik (Master of Science) | Gesamtkonto | Hauptseminar, Projekt, Masterarbeit | Projekt Modul | AI-1 Systems Project)

Studien-/Prüfungsleistungen:

AI-1 Systems Project (Prüfungsnummer: 31161)

Prüfungsleistung, Praktikumsleistung, benotet, 10 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

weitere Erläuterungen:
Method of Examination: Working software, competition/benchmark results, project reports, presentations (for all sub-projects). Grading: Software/Results: 60%, 25% project report, 15% presentation.

Prüfungssprache: Englisch

Erstablegung: WS 2022/2023, 1. Wdh.: SS 2023

1. Prüfer:

Michael Kohlhase