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Cited by 425

The DOI matches its OpenAlex record; 13 of the 13 references it cites were found in a registry or an index.

Brain Meets Brawn: Why Grid and Agents Need Each Other

Ian T Foster, Nicholas R. Jennings, Carl Kesselman·2004·Adaptive Agents and Multi-Agents Systems

Abstract

The Grid and agent communities both develop concepts and mechanisms for open distributed systems, albeit from different perspectives. The Grid community has historically focused on brawn: infrastructure, tools, and applications for reliable and secure resource sharing within dynamic and geographically distributed virtual organizations. In contrast, the agents community has focused on brain: autonomous problem solvers that can act flexibly in uncertain and dynamic environments. Yet as the scale and ambition of both Grid and agent deployments increase, we see a convergence of interests, with agent systems requiring robust infrastructure and Grid systems requiring autonomous, flexible behaviors. Motivated by this convergence of interests, we review the current state of the art in both areas, review the challenges that concern the two communities, and propose research and technology development activities that can allow for mutually supportive efforts.

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Metadata

Authors
Foster, I. T., Jennings, N. R., & Kesselman, C.
Venue
Adaptive Agents and Multi-Agents Systems
Published
2004-01-01
Pages
8-15
ISSN
1548-8403 (ISSN-L)
OpenAlex
W2169398118
Cited by
425
References
13
FWCI
78.15
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Brain Meets Brawn: Why Grid and Agents Need Each Other. https://app.cochat.ai/papers/10.1109/aamas.2004.78
The paper
Foster, I. T., Jennings, N. R., & Kesselman, C. (2004). Brain Meets Brawn: Why Grid and Agents Need Each Other. Adaptive Agents and Multi-Agents Systems. https://doi.org/10.1109/aamas.2004.78

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.