AINeutralarXiv – CS AI · Mar 44/102
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Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search
Researchers developed AIGB-Pearl, a new AI-driven auto-bidding system that combines generative planning with policy optimization to improve advertising performance. The system addresses limitations of existing offline reinforcement learning methods by incorporating a trajectory evaluator and safe exploration mechanisms beyond static datasets.