New AI research to improve the intelligence of AI agents by an improved Process Reward Model (PRM). Integration of MCTS and Q-Net for advanced Q-Values: dense step-by-step Q scores for an optimal reasoning and decision process by the AI Agent - without a final reward function.
All rights w/ authors:
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
by Zongyu Lin, Yao Tang, Xingcheng Yao, Da Yin, Ziniu Hu, Yizhou Sun, Kai-Wei Chang
from University of California, Los Angeles, USA and
Shanghai Jiaotong University, Shanghai, China.
#airesearch
#reasoning
#aiagents