Estimating Central, Peripheral, and Temporal Visual Contributions to Human Decision Making in Atari Games
We study how different visual information sources contribute to human decision making in dynamic visual environments. Using Atari-HEAD, a large-scale Atari gameplay dataset with synchronized eye-tracking, we introduce a controlled ablation framework as a means to reverse-engineer the contribution of peripheral visual information, explicit gaze information in the form of gaze maps, and past-state information from human behavior. We train action-prediction networks under six settings that selectively include or exclude these information sources. Across 20 games, peripheral information shows by far the strongest contribution, with median prediction-accuracy drops in the range of 35.27-43.90%...
| Authors | Henrik Krauss, Takehisa Yairi |
|---|---|
| Primary category | cs.LG |
| Published | 6 April 2026 |
| Last updated at source | 2 June 2026 |
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