Unverified50% confidenceFactExact time
In the Agent context, reinforcement learning (RL) is mainly used to optimize decision-making policies, with commonly used methods including RLHF and DPO; compared with supervised fine-tuning, it can explore better paths through trial and error, but it faces challenges such as difficulty in reward design, low sample efficiency, and unstable training.
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50%
Confidence
Medium-term (~90 days)
Relevance
10/14/2026
First Seen
Valid until: 1/12/2027
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