Agentic Discovery: Closing the Loop With Cooperative Agents
As data-driven methods, artificial intelligence, 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. Cooperative agents can augment the role of humans and enable autonomous discovery.
Authors
- Ian Foster (ORCID: https://orcid.org/0000-0003-2129-5269)
- Kyle Chard (ORCID: https://orcid.org/0000-0002-7370-4805)
- J. Gregory Pauloski (ORCID: https://orcid.org/0000-0002-6547-6902)
Institutions
- University of Chicago (US)
Publication Details
- Journal
- Computer
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1109/mc.2025.3575029
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00