GAIG Game AI Research Group @ QMUL

Metagame Autobalancing for Competitive Multiplayer Games

2020
Hernandez, Daniel and Gbadamosi, Charles Takashi Toyin and Goodman, James and Walker, James Alfred

Abstract

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.
URL: https://ieeexplore.ieee.org/document/9231762

Cite this work

@inproceedings{hernandez2020metagame,
author= {Hernandez, Daniel and Gbadamosi, Charles Takashi Toyin and Goodman, James and Walker, James Alfred},
title= {{Metagame Autobalancing for Competitive Multiplayer Games}},
year= {2020},
booktitle= {{IEEE Conference on Games (CoG)}},
pages= {275--282},
url= {https://ieeexplore.ieee.org/document/9231762},
abstract= {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.},
}

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