Using gaming environments to teach the idea and application of CBR

Pascal Reuss, Klaus-Dieter Althoff

In: Thomas Seidl (editor). Lernen, Wissen, Daten, Analysen. GI-Workshop-Tage "Lernen, Wissen, Daten, Analysen" (LWDA-2021) September 1-3 Munich Germany CEUR 2021.


Bringing the idea of artificial intelligence (AI) methods to students can sometimes be a challenging task, especially with focus on motivation, simplicity, and understanding. This paper describes a platform in development that uses several modules with different gaming scenarios like a First-Person scenario or the board game Settlers of Catan in which Case-based Reasoning (CBR) can be used to solve the given problems and win the game. The idea behind this platform is to make the task of teaching and learning the idea of software agents, CBR, and their application to given problems more flexible and interesting for both, students and lecturers. We describe the general architecture of the platform and take a closer look on existing modules with their scenarios and CBR solutions. In addition, we present a visualization module to support the traceability of decisions made by the AI.

Weitere Links

paper_37.pdf (pdf, 1 MB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz