Toward Autonomous Digital Agents in the Real World İzzeddin Gür Google Deepmind
Abstract: Reinforcement Learning (RL) provides a mathematically grounded foundation for sequential decision-making. Yet, deploying RL agents for real-world digital tasks remains a significant challenge. Contemporary web pages present unstructured state spaces that exhibit long-context HTML code with high perceptual noise, lack of reward feedback, and active safety me…
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