VEG: Verbal ϵ -greedy for Semantic Exploration in Multi-Turn RL Agents
This work proposes VEG (verbal ϵ -greedy), a novel framework that leverages external feedback as a dynamic control variable to explicitly balance exploration and exploitation within the semantic space and achieves superior accuracy compared to standard RL baselines.
Yongchang Hao, Jie Hao, Yongsheng Mei et al.
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