RPG Dreamer: Towards Agent-Driven Generation of Long-Horizon Interactive Worlds

Games, as a special category of software, create interactive worlds governed by their own specific rules. Given the recent successes of coding agents, increasing attention is devoted to automatic game generation. We observe that existing methods fail to create long-horizon games, as they entangle game mechanics with content and lack effective playtesting capabilities. In this work, we present RPG Dreamer, a framework capable of generating games with hours-long coherent playthroughs. We use role-playing games (RPGs) to exemplify the long-horizon generation capabilities of the framework, as RPGs feature branching narratives, non-linear progressions, and extended playtime. RPG Dreamer consists of an Agent-Oriented Game Engine (AOGE) and a Reviewer-centric Generation Loop (RGL). AOGE separates mechanics from content and exposes an agent interface with uniform observation and semantic action, enhancing both the reliability and coverage of automated gameplay. RGL is a closed-loop pipeline that enables agents to iteratively generate, review, and evolve games through a multi-reviewer system, including a team of gameplay reviewers who conduct playtesting to expose latent bugs. Due to the absence of benchmarks for evaluating hour-scale game generation, we further propose RPG-Bench, a benchmark of 150 evaluation instances spanning diverse themes, whose metrics are grounded in dynamic gameplay trajectories. Results on RPG-Bench demonstrate that RPG Dreamer improves the scalability of state-of-the-art coding agents on long-horizon games.