GameWAM: A World Action Model for Video Games
Modern video games combine first-person perception, rapid visual changes, persistent world state, and heterogeneous native controls. Existing game agents map visual and task context directly to actions but lack explicit world dynamics modeling, whereas interactive game world models predict visual futures from supplied actions but do not serve as task policies. World-Action Models (WAMs) unify these objectives, but remain largely unexplored under the dynamics and open-ended interaction of video games. We introduce GameWAM, to our knowledge the first WAM for native closed-loop gameplay and GUI control. GameWAM jointly generates future visual observations and executable keyboard-mouse trajec...
| Authors | Yuncheng Guo, Zhanqiu Zhang, Yiwen Guo et al. |
|---|---|
| Primary category | cs.AI |
| Published | 25 August 2026 |
| Last updated at source | 10 September 2026 |
Connected in the knowledge graph
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Models and datasets referencing this paper
- Yunncheng/gamewam-vizdoomDataset
- Yunncheng/gamewam-minecraftDataset
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