AINeutralarXiv – CS AI · Jun 46/10
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Success Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
Researchers prove that success conditioning—a widely-used policy improvement technique in machine learning—solves a specific trust-region optimization problem with automatic regularization. The method emerges as a conservative improvement operator that cannot degrade performance, making it theoretically sound for applications like reinforcement learning and imitation learning.