A New Rules Balance Track for the Pokémon VGC AI Competition 2.0

The VGC AI Competition is a unified vehicle for designing and testing AI agents in game design and gameplayrelated tasks, specifically within Pokémon. In this competition, players must both strategically battle to maximize their win rate and anticipate their opponents’ teams to improve their chances of victory before the battles. In this paper, we expand the existing competition by introducing a new track centered on a novel game balance issue, Rules Balance. Rather than modifying game units to encourage specific usage rates of Pokémon or teams during a competitive season, the focus is on reconfiguring the Pokémon battle rules to incentivize non-damaging moves (moves with delayed rewards) by rational agents. This AI assistant tool relieves game designers of the costly and time-consuming task of testing numerous parameter combinations to achieve desired move usage patterns. This allows designers to allocate more time to the creative process of developing new game mechanics. We present and evaluate an initial agent based on a genetic search that competes against a tree-search battle agent. While the battle agent is motivated to devise the most efficient plan of action to win, the balance agent adjusts the rule parameters to encourage the rational agent to use specific desired moves.