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Paper · arXiv

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...

AuthorsYuncheng Guo, Zhanqiu Zhang, Yiwen Guo et al.
Primary categorycs.AI
Published25 August 2026
Last updated at source10 September 2026
cs.AIcs.CVcs.LG
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