No Player Left Behind: Evolving Dungeons and Dragons Combat to Optimize Difficulty and Player Contributions
Year: 2024
Type: conference-paper
Abstract: Creating well-balanced combat encounters can be a difficult task for Game Managers (GMs) in tabletop games such as Dungeons and Dragons (DnD). This work uses a simulation environment to generate new sets of DnD encounters that can be optimized for both difficulty and balance among player contributions. Encounters are evaluated using simulated games that can either be run probabilistically (using dice rolls) or with deterministic expected outcomes. While the expected approach allows game outcomes to be simulated substantially faster and is a good estimate of difficulty, it is a less reliable measure of balance. A genetic algorithm was used to generate encounters that meet the desired difficulty and where all players are needed for success.
Authors: Fiona Shyne, Seth Cooper
Institution: Northeastern University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404445390