A semantic multi-agent system for intelligent and adaptive scientific workflows

Authors:
Zhili Zhao;Adrian Paschke
Affiliations:
Freie Universität Berlin, Germany;Freie Universität Berlin, Germany
Venue:
Proceedings of the 4th International Workshop on Semantic Web Applications and Tools for the Life Sciences
Year:
2011

Citing 3
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Abstract

Flexibility and adaptability are regarded as the important challenges of scientific workflows. In this paper, we propose a flexible scientific workflow system using a rule-based semantic multi-agent system to handle failures, exceptions, and dynamic changes. The approach provides advantages such as making decisions at runtime, collaboration between organizations, provenance, result explanation, etc.