English

Agentic Discovery: Closing the Loop with Cooperative Agents

Multiagent Systems 2025-10-16 v1 Artificial Intelligence

Abstract

As data-driven methods, artificial intelligence (AI), and automated workflows accelerate scientific tasks, we see the rate of discovery increasingly limited by human decision-making tasks such as setting objectives, generating hypotheses, and designing experiments. We postulate that cooperative agents are needed to augment the role of humans and enable autonomous discovery. Realizing such agents will require progress in both AI and infrastructure.

Keywords

Cite

@article{arxiv.2510.13081,
  title  = {Agentic Discovery: Closing the Loop with Cooperative Agents},
  author = {J. Gregory Pauloski and Kyle Chard and Ian T. Foster},
  journal= {arXiv preprint arXiv:2510.13081},
  year   = {2025}
}

Comments

Published in IEEE Computer Volume 58 Issue 10

R2 v1 2026-07-01T06:37:59.971Z