Published on October 14, 2025, the study examines data, algorithms, and reasoning modes in reinforcement learning for agents, including trajectories and tool use.
Published on October 14, 2025, the article investigates reinforcement learning for agents across three dimensions: data, algorithm design, and reasoning modes. It presents findings on trajectory data and tool use, and reports an open-source repository.
The study may interest engineers assessing approaches to training language-model agents for reasoning and tool use. To learn about the findings and verify their scope, consult the original article and the cited repository; review the methods, data, and reported results there, without assuming details not specified in the summary.