GameDirector: Decoupling Gameplay Logic from Rendering for Player-Configurable Game World Models
cs.CV
Submitted: 2026-09-22
Updated: 2026-09-22
Comments: Project Page: https://jimntu.github.io/gamedirector/
Project page: https://jimntu.github.io/gamedirector
License: http://creativecommons.org/licenses/by/4.0/
The gist: Recent game world models support realistic visual simulation and interactive gameplay based on player inputs.
Terminology
Abstract
Recent game world models support realistic visual simulation and interactive gameplay based on player inputs. However, they typically learn environment dynamics from pixel-level supervision, jointly modeling perception, memory, state transitions, and rendering within a single end-to-end framework. While this design enables open-ended, action-controllable generation, it still falls short of delivering a complete gameplay experience. Games are governed by explicit mechanics, such as health deduction, skill activation, combat rules, and termination conditions. These mechanics depend on precise and consistent state transitions that generative models alone cannot reliably enforce. In contrast, game engines can guarantee such mechanics through hard-coded rules, but provide limited flexibility for player-driven creation. To bridge these paradigms, we introduce GameDirector, the first agentic framework that decouples rule-based gameplay logic from visual rendering. Given player-defined configurations, the framework acts as an intelligent director that interprets visual observations, updates game states, tactically controls NPCs, and enforces gameplay rules. It then translates these decisions into text prompts that guide the video world model to render the resulting gameplay. This separation allows players to configure characters, states, and rules much like a game developer while preserving coherent game mechanics. Experiments on three games, using data collected by our automated gameplay agent, show that GameDirector achieves accurate state tracking, reliable rule following, and improves boss action quality by more than 39.9% over various end-to-end game world model settings. Overall, by externalizing player-controllable game logic, GameDirector establishes a middle ground between hard-coded simulation and generative modeling, enabling more flexible and closed-loop gameplay experiences.
Sources
- H3-World: Turning Language Understanding into World Control
- Code World Model: Coding Agent as World Brain
- UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining
- Infinite Worlds with Versatile Interactions
- Matrix-game 2.0: An open-source, real-time, and streaming interactive world model
- Programmable World Model
- WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG
- From Pixels to States: Rethinking Interactive World Models as Game Engines
- StatePlay: State-Aware Game World Models for Mechanics-Consistent Generation
- AI for Games in the Foundation Model Era
- Lyra 2.0: Explorable Generative 3D Worlds
- DreamX-World 1.0: A General-Purpose Interactive World Model
- Gemma 4 Technical Report
- InSpatio-WorldFM: An Open-Source Real-Time Generative Frame Model
- Advancing Open-source World Models
- SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models
- Wan: Open and Advanced Large-Scale Video Generative Models
- ReactiveGWM: Flexible Control and NPC Reactivity in Game World Models
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