Details of Grant 

EPSRC Reference:	EP/V048740/2
Title:	Evolutionary Optimisation of Networks towards Complexity
Principal Investigator:	Claussen, Dr J
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	School of Computer Science
Organisation:	University of Birmingham
Scheme:	Standard Research - NR1
Starts:	01 November 2021	Ends:	31 August 2023	Value (£):	185,946
EPSRC Research Topic Classifications:	Non-linear Systems Mathematics
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:
Summary on Grant Application Form
Network science provides systematic approaches of introducing more complexity in the interaction topology, compared to random graphs as introduced by Erdös and Renyi. In which biological systems does a higher complexity result in improved resilience or other evolutionary benefits? Can this perspective provide insight for improving processes in technology and society? This project takes the novel approach of utilising network complexity measures to generate ensembles of networks of increasing complexity, followed up by an investigation into how network complexity influences the complexity of the resulting network dynamics. This approach is motivated by a common implicit hypothesis that complex structures are beneficial for adaptive systems, and aims to translate back beneficial complex network topologies into specific applications. It is expected that increased complexity can have a beneficial impact (as in networks evolved in nature), or might impede functionality (expected to appear in logistic or production networks) where benefits of resilience and adaptivity come at organisational costs of a more complex structure. The project therefore includes two application-oriented dynamical modelling studies where increased network performance from higher complexity is expected, but also investigates cases which might challenge the generality of such a paradigm.
Key Findings
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Organisation Website:	http://www.bham.ac.uk