VGC AI Competition - A New Model of Meta-Game Balance AI Competition

• Type: Article in International Conference Proceedings Book
• Date: 2021

Authors

Reis, S (Author) Other; reis, lp (Author) FEUP; lau, n (Author) Other

Conference proceedings International

Title: 2021 IEEE Conference on Games (CoG), Copenhagen, Denmark, August 17-20, 2021

Pages: 31-38

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00W-0NY

DOI: 10.1109/cog52621.2021.9618985

Abstract (EN): This work presents a framework for a new type of meta-game balance AI Competition based on Pokemon. Pokemon battles can be viewed as adversarial games played by AIs. Around these games, there is also a meta-game: which Pokemon to include in a team for battles, which moves to pick for every Pokemon in the team, etc. This meta-game is itself a game with a set of rules that govern which Pokemon and which moves are available in the roster that can be selected from, or which attributes (health points, damage, etc.) a Pokemon or moves should have. The aim of the framework is to facilitate competitions in creating the most balanced meta-game possible; one where there is a large variety of Pokemon and moves to choose from, and many possible combinations that are effective. AI agents could assist human designers in achieving strategically expressive meta-games, and this type of benchmark could incentivize game designers and researchers alike to advance knowledge on this type of domain.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8