| EPSRC Reference: |
EP/C549392/1 |
| Title: |
Understanding Emergent Behaviours in Complex Systems |
| Principal Investigator: |
Bai, Dr L |
| Other Investigators: |
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| Department: |
School of Computer Science |
| Organisation: |
University of Nottingham |
| Scheme: |
Discipline Hopping Pre-FEC |
| Starts: |
01 April 2005 |
Ends: |
30 September 2005 |
Value (£): |
36,282
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| EPSRC Research Topic Classifications: |
| Fundamentals of Computing |
Logic & Combinatorics |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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This proposal is a request for funds to support Dr Bai at the School of Computer Science & IT, University of Nottingham in a 6 month placement at the Department of Mathematics, Imperial College London, to work with Professor Henrik Jensen (see attached CV for details) on an innovative and adventurous research programme - Understanding Emergent Behaviours in Complex Systems. The two parties have never collaborated in any way before. The Hopping Award provides an excellent opportunity for us to gain the support we need.We aim to investigate a different approach to study complex behaviours. In particular, it aims to investigate the role that complexity theories and mathematical physics can play in understanding and governing complex processes, for which, the termites are an example. In other words, it aims to understand how complex behaviours can emerge from simple rules and actions of agents and the connection between emergent behaviour and complexity. The answers to this may lie in the mathematical science of complexity theories, evolution processes, chaos, fractals or pattern formation systems. Computational models allow us to exploit several different scenarios and to obtain proofs of convergence and other formal results about the behaviour of the system. Mathematical models of complex phenomena can be used to shed light onto them. A more accurate understanding of bio-inspired complex systems can lead to the design of a more effective computational intelligence algorithm. The fundamental question is if there is any mathematical theory or model(s) that would allow us to understand the underlying mechanisms and so better control complex multi-agent systems.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.nottingham.ac.uk |