10 citations · 19 across the 4 of their papers we have counts for
6 papers
Toxicity in Twitch Chats: An LLM-Based Analysis Across Gaming Communities
Ronja Fuchs, Florian Rupp, Timo Bertram +2
Toxicity in online gaming communities remains a persistent challenge, manifesting across genres, platforms, and player interactions. While much research is focused on in-game toxic…
Level the Level: Balancing Game Levels for Asymmetric Player Archetypes With Reinforcement Learning
Florian Rupp, Kai Eckert
Balancing games, especially those with asymmetric multiplayer content, requires significant manual effort and extensive human playtesting during development. For this reason, this…
Simulation-Driven Balancing of Competitive Game Levels with Reinforcement Learning
Florian Rupp, Manuel Eberhardinger, Kai Eckert
The balancing process for game levels in competitive two-player contexts involves a lot of manual work and testing, particularly for non-symmetrical game levels. In this work, we f…
It might be balanced, but is it actually good? An Empirical Evaluation of Game Level Balancing
Florian Rupp, Alessandro Puddu, Christian Becker-Asano +1
Achieving optimal balance in games is essential to their success, yet reliant on extensive manual work and playtesting. To facilitate this process, the Procedural Content Generatio…
G-PCGRL: Procedural Graph Data Generation via Reinforcement Learning
Florian Rupp, Kai Eckert
Graph data structures offer a versatile and powerful means to model relationships and interconnections in various domains, promising substantial advantages in data representation,…
GEEvo: Game Economy Generation and Balancing with Evolutionary Algorithms
Florian Rupp, Kai Eckert
Game economy design significantly shapes the player experience and progression speed. Modern game economies are becoming increasingly complex and can be very sensitive to even mino…