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cs.LG2026
An Explicit Feedback Contract for Iterative ML-Agent Harnesses
Kehui Yao, Chuanbo Hu, Jiao Chen +8
Iterative ML agents develop models by editing code, running experiments, reading a validation score, and choosing what to try next. In current harnesses this loop is served by an e…
cs.LG2023
Dynamic Decision Making in Engineering System Design: A Deep Q-Learning Approach
Ramin Giahi, Cameron A. MacKenzie, Reyhaneh Bijari
Engineering system design, viewed as a decision-making process, faces challenges due to complexity and uncertainty. In this paper, we present a framework proposing the use of the D…