EPSRC Reference: |
GR/S63090/01 |
Title: |
Coping with Complexity: Multi-disciplinary methods to model, measure, control and predict the behaviour of complex, dynamic networks |
Principal Investigator: |
Smart, Dr JH |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Engineering Science |
Organisation: |
University of Oxford |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
24 July 2003 |
Ends: |
23 January 2004 |
Value (£): |
47,057
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EPSRC Research Topic Classifications: |
Artificial Intelligence |
Complexity Science |
Networks & Distributed Systems |
New & Emerging Comp. Paradigms |
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EPSRC Industrial Sector Classifications: |
Communications |
Electronics |
Information Technologies |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
We propose to develop a research cluster that is centred on modelling complex systems as networks of interacting agents. Real-world examples of such systems include financial markets, manufacturing supply chains and living organisms. The complex dynamics generated by non-linear interactions between agents in these systems make them challenging to predict and control. In addition, such systems are frequently characterised by poor quality information, which makes them difficult to measure and model. However, it is also known that such systems can operate effectively and robustly, adapting the structure of the network and the behaviour of the components to the environment. This project will develop a detailed research cluster proposal or proposals on the theme of Coping with Complexity that will compare the models and methods that have been developed in the fields of mathematics, engineering, biology and business studies.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.ox.ac.uk |