arXiv AI
Aug 12
Recovering Wasted Compute in Autoresearch Agents
arXiv:2608. 10424v1 Announce Type: new Abstract: A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch.
Autoresearch in Mixed-Integer Linear and Nonlinear Programming
The paper introduces AutoMIP, a reusable agent skill designed to manage long‑horizon autoresearch for mixed‑integer linear and nonlinear programming problems. AutoMIP combines idea pooling with an algorithm tree search to maintain a persistent pool of complementary candidate ideas and organize experiments into a structured tree, allowing the agent to preserve unexplored hypotheses, refine promising algorithms, and switch methodological directions based on historical states. Experiments on MILP and MINLP benchmark cohorts show that AutoMIP achieves the highest final success rates, discovering new best solutions for 31 of 60 MIPLib instances and 52 of 60 MINLPLib instances, and ablation studies confirm the complementary contributions of idea pooling and algorithm tree search.
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