Metagame Autobalancing for Competitive Multiplayer Games
This addresses game design challenges for developers by enabling more nuanced balancing in multiplayer scenarios, though it is incremental as it builds on existing simulation-based optimization methods.
The paper tackles the problem of balancing competitive multiplayer games by introducing a tool that allows designers to specify sophisticated meta-game balance targets beyond equal win chances, and demonstrates its effectiveness on examples including Rock-Paper-Scissors and an asymmetric fighting game.
Automated game balancing has often focused on single-agent scenarios. In this paper we present a tool for balancing multi-player games during game design. Our approach requires a designer to construct an intuitive graphical representation of their meta-game target, representing the relative scores that high-level strategies (or decks, or character types) should experience. This permits more sophisticated balance targets to be defined beyond a simple requirement of equal win chances. We then find a parameterization of the game that meets this target using simulation-based optimization to minimize the distance to the target graph. We show the capabilities of this tool on examples inheriting from Rock-Paper-Scissors, and on a more complex asymmetric fighting game.