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Advanced Training Environments for Interactive AI Agents

Agents need interactive worlds for reinforcement learning; high-quality simulations replace costly real-world data collection.

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Example

Train a web-navigation agent: a procedural simulator generates varied page layouts, bridge with human video demos for realistic clicking and scrolling, then evaluate transfer to real browsers where success rates exceed 85%.

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