I built an Android-like OS that runs in the browser
MobileGym is a new simulation platform designed for mobile GUI agent research, enabling online reinforcement learning training and deterministic evaluation. It successfully simulates 28 mobile apps in a browser environment, providing a reliable reward signal with no false judgments. The platform addresses key challenges of real-device pipelines by allowing for structured state replication and consequence-free testing.
- ▪MobileGym covers 28 mobile apps, including 12 daily and 16 system apps.
- ▪The platform achieves a 95.1% retention rate of simulation gains on real devices.
- ▪It allows for rapid app integration with minimal changes required to the OS or benchmark layer.
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TL;DR MobileGym is a verifiable and highly parallel simulation platform for mobile GUI agent research — the first to make online RL training and deterministic evaluation feasible on real-world daily apps, long a structural blind spot of real-device pipelines. It covers 28 mobile apps (12 daily + 16 system) in the browser. Across the released validation suite, programmatic state judges show no false accept/reject cases over 416 parameterized task templates (vs. 10.2% misjudgment when the same real-device trajectories are scored by a VLM), giving a clean RL reward signal; structured state replication (∼400 MB per browser instance) makes single-machine batch-parallel GRPO cheap.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Mobilegym.
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