The authors tested ProVer on ALFWorld, WebShop and SearchQA, which cover embodied household tasks, online shopping and search-based question answering.
Verifying pivotal agent decisions improves reinforcement learning credit assignment
ProVer uses a model to identify consequential action segments, then validates their value through sampled outcomes before assigning extra training credit.
Big Tech
Dongwon Jung · Hemanth Neelgund Ramesh · Yifan Wang · Xiaomin Li · Yuexing Hao · Yu Hu · +4 more
University of California, Davis · Microsoft · University of Washington · Purdue University
Research Digest··2 min read
Jung et al.
Why this paper
From Microsoft and 3 others
In one line
Distributing credit only to pivotal decision segments improves large language model agent reinforcement learning outcomes.
What we could check
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