Exploring Gameplay With AI Agents
This work addresses the challenge of efficient and objective playtesting for game designers, though it is incremental as it applies existing agent-based simulation methods to a new domain.
The paper tackled the problem of subjective, expensive, and incomplete game playtesting by developing an automated agent-based approach that simulates game mechanics to explore the game space and collect data for designers. The agent played in minutes what would take testers days, analyzing thousands of simulations to expose imbalances, identify inconsequential rewards, and evaluate strategic choices, leading to design changes that improved player experience in The Sims Mobile.
The process of playtesting a game is subjective, expensive and incomplete. In this paper, we present a playtesting approach that explores the game space with automated agents and collects data to answer questions posed by the designers. Rather than have agents interacting with an actual game client, this approach recreates the bare bone mechanics of the game as a separate system. Our agent is able to play in minutes what would take testers days of organic gameplay. The analysis of thousands of game simulations exposed imbalances in game actions, identified inconsequential rewards and evaluated the effectiveness of optional strategic choices. Our test case game, The Sims Mobile, was recently released and the findings shown here influenced design changes that resulted in improved player experience.