Computational Modelling Group

A Connected Island: how the Iron Curtain affected Archaeologists in Central Europe

Iza Romanowska

Using citation network analysis this project aims to investigate the effects that the Cold War had on researchers on both sides of the Iron Curtain.

Adding social ties to the Schelling model

Seth Bullock, Sally Brailsford (Investigators), Elisabeth zu-Erbach-Schoenberg

The Schelling model is an abstract model for segregation in
a spatially arranged population. We extended the traditional model by the addition of a dynamic social network. The social network influences the spatial dynamics of agents moving on the grid by changing the agents’ evaluation of their neighbourhood. In turn, the spatial arrangement influences the change of the social network.

Amorphous Computation, Random Graphs and Complex Biological Networks

Seth Bullock (Investigator)

This interdisciplinary research collaboration arose within the Simple Models of Complex Networks research cluster funded by the EPSRC www.epsrca.ac.uk through the Novel Computation Initiative. Here, leading groups from the Universities of Leeds, Sheffield, Nottingham, Southampton, Royal Holloway and King’s College and industrial partners BT are brought together for the first time to develop novel amorphous computation methods based on the theory of random graphs.

An Evolutionary Economic Approach to the Household?

Jason Hilton

The household is a fundamental societal unit. In a huge array of contexts, our understanding of social behaviour relies on an interpretation of how decision are taken at the household level.This work aims to model individual decision-making and interactions between individuals explicitly within the framework of agent-based modelling, following the work of Potts (2000). Potts describes how economic problems can better be dealt with by considering how agents with incomplete, evolving preferences in the form of decision rules interact on a network, and how they cooperate and form ties to produce combinatorial technologies. Following the work of Gary Becker, he then considers how this ostensibly economic framework might hypothetically describe partnership search and household formation and dissolution.

An investigation in to the effects of information provision on driver learning

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

This work aims to better understand and model the role of individual learning and experience on driver route choice. We intend to demonstrate that vehicle-driver agent based models stand alone in being able to capture the complex reciprocal interactions between drivers and their environment, and allow us to incorporate the effects of prior knowledge from previous trips and advice from official information sources and social networks.

An Investigation into the Cascade Effect of Mergers on the Global Financial Markets

Seth Bullock, Antonella Ianni (Investigators), Camillia Zedan

An investigation into the external effects that horizontal mergers have on the interconnected global markets.

Associative learning in ecosystems: Network level adaptation as an emergent propery of local selection

Richard Watson, James Dyke (Investigators), Daniel Power

Ecosystems may exhibit collective adaptive properties that arise from natural selection operating on their component species. These properties include the ability of the ecosystem to return to specific configurations of species, in a manner highly analogous to mechanisms of associative learning in neural networks.

Bayesian Agent-Based Population Studies: Transforming Simulation Models of Human Migration

This is a cutting-edge project in demographic methodology, funded by the European Research Council (ERC), through the Consolidator Grant ERC-CoG-2016-725232. Its aim is to develop a ground-breaking simulation model of international migration, based on a population of intelligent, cognitive agents, their social networks and institutions, all interacting with one another. The project also aims to transform the study of migration – one of the most uncertain population processes and a top-priority policy area – by offering a step change in the way it can be understood, predicted, and managed.

Bayesian Agents as Models for the Disclosure Behaviour of Pregnant Drinkers

Seth Bullock, Jakub Bijak (Investigators), Jonathan Gray

Examining the feasibility of signalling games, played by Bayesian decision theoretic agents as a model for the disclosure of drinking behaviour by pregnant women to their midwives.

BRECcIA - Building REsearch Capacity for sustainable water and food security In sub-saharan Africa

The BRECcIA project is aimed at developing research and researchers to understand water and food security challenges in sub-Saharan Africa

Care Life Cycle

Seth Bullock, Sally Brailsford, Jason Noble, Jakub Bijak (Investigators), Elisabeth zu-Erbach-Schoenberg, Jason Hilton, Jonathan Gray

This research programme brings together teams of researchers from social sciences, management science and complexity science to develop a suite of models representing the socio-economic and demographic processes and organisations implicated in the UK’s health and social care provision. Integral to the project is working with our partners in the public sector and communicating the results of these models to policymakers allowing them to effectively plan for the future.

Centre for Doctoral Training in Next Generation Computational Modelling

Hans Fangohr, Ian Hawke, Peter Horak (Investigators), Susanne Ufermann Fangohr, Thorsten Wittemeier, Kieran Selvon, Alvaro Perez-Diaz, David Lusher, Ashley Setter, Emanuele Zappia, Hossam Ragheb, Ryan Pepper, Stephen Gow, Jan Kamenik, Paul Chambers, Robert Entwistle, Rory Brown, Joshua Greenhalgh, James Harrison, Jonathon Waters, Ioannis Begleris, Craig Rafter

The £10million Centre for Doctoral Training was launched in November 2013 and is jointly funded by EPSRC, the University of Southampton, and its partners.

The NGCM brings together world-class simulation modelling research activities from across the University of Southampton and hosts a 4-year doctoral training programme that is the first of its kind in the UK.

CRISIS – Complexity Research Initiative for Systemic InstabilitieS

Frank McGroarty (Investigator), Bob De Caux

A new approach to modelling and understanding financial system and macroeconomic risk and instability

DIPLOS - Dispersion of Localised Releases in a Street Network

Trevor Thomas, Ian Castro (Investigators)

The security threat level from international terrorism, introduced by the UK Security Service, has been classified as either "severe" or "critical" for much of its six-year history, and currently remains as "substantial" (source: MI5 website). Part of the risk posed by terrorist threats involves potential releases of air-borne chemical, biological, radiological or nuclear (CBRN) material into highly populated urbanised areas. Smoke from industrial accidents within or in the vicinity of urban areas also pose risks to health and can cause widespread disruption to businesses, public services and residents. The Buncefield depot fire of 2005 resulted in the evacuation of hundreds of homes and closure of more than 200 schools and public buildings for two days; consequences would have been much more severe if prevailing meteorological conditions had promoted mixing or entrainment of the smoke plume into the urban canopy. In both these scenarios it is crucial to be able to model, quickly and reliably, dispersion from localised sources through an urban street network in the short range, where the threat to human health is greatest. However, this is precisely where current operational models are least reliable because our understanding and ability to model short-range dispersion processes is limited. The contribution that DIPLOS will make is:

1. to fill in the gaps in fundamental knowledge and understanding of key dispersion processes,
2. to enable these processes to be parametrized for use in operational models,
3. to implement them into an operational model, evaluate the improvement and apply the model to a case study in central London

Most of the existing research on urban dispersion has focused on air quality aspects, with sources being extensive and distributed in space. Scientifically, this research is novel in focusing on localized releases within urban areas, and on dispersion processes at short range. Through a combination of fundamental studies using wind tunnel experiments and high resolution supercomputer simulations, extensive data analysis and development of theoretical and numerical models, DIPLOS will contribute to addressing this difficult and important problem from both a scientific research and a practical, operational perspective.

Evolving Resilience to Leverage Based Crashes

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

This project analyses the maturation, initiation and evolution of crashes in the financial markets using an agent-based model.

Excitable Boys: An Exploration of the Role of Social Groups in the Self-radicalisation Process Using Agent-based Modelling.

Jason Noble (Investigator), Lewys Brace

This work built upon the seminal work of Sageman (2008), and his hypothesis that the self-radicalisation phenomenon that we are currently witnessing across Europe and the United States stems from self-organising ‘bunches of guys’. More specifically, there was a focus on how individuals can influence one another through social links; and how this can lead to behaviour, similar to deindividuation, arising through their interactions. Complexity theory and agent-based modelling were used in order to explore the interactions that are believed to lie at the heart of this psycho-social phenomenon, and justification is given for this approach. The model presented demonstrated that social bonds can lead to a greater number of individuals ‘rebelling’ against the status quo.

Fracturing of small social networks

Seth Bullock, Sally Brailsford (Investigators), Elisabeth zu-Erbach-Schoenberg

A connected social network is a very important factor for the success of groups and organisations. We investigate which factors make a group more resistant to the effects of disagreements which commonly happen in small social networks.

FUE: Foragers in Unpredictable Environments

Iza Romanowska

An Agent-based model developed to investigate human dependencies on orally transmitted knowledge under constantly changing environmental conditions.

Generic Operational Simulation of Civil Unmanned Air Vehicle Operations

Hans Fangohr, James Scanlan (Investigators)

This project creates a generic operational simulation of Unmanned Air Vehicle Operations. UAVs can be valued for their mission-suitability and compared against various configurations.

Integrating Automated Vehicles into the Transport Network

Bani Anvari, Ben Waterson (Investigators), Craig Rafter

Innovative new designs to transportation infrastructure - with a strong evidence base - that will support automated vehicles to maximize sustainability in the transport network.

It takes all sorts: the mathematics of people’s behaviour in financial markets

Valerio Restocchi (Investigator), Frank McGroarty, Enrico Gerding

Agent-based models provide a deeper understanding of financial markets than classic models. We model people's behaviour and use agent-based simulations to study financial markets. By analysing the emerging complex dynamics, we achieve a deeper understanding of market participants' behaviours, which are necessary for a deeper comprehension of financial markets themselves.

Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction

Mahesan Niranjan, Andrew Collins, Reuben Pengelly (Investigators)

This iPhD project uses a Gaussian Bayesian Networks framework through Machine learning methods to predict which genes are involved in the development of different diseases.

Mathematical tools for analysis of genome function, linkage disequilibrium structure and disease gene prediction

Andrew Collins, Mahesan Niranjan, Reuben Pengelly (Investigators), Alejandra Vergara Lope

This iPhD project uses a Gaussian Bayesian Networks approaches framework through machine learning approach to predict which genes are involved in the development of different diseases.

Modelling the Easterlin Effect

Jason Hilton

This project is an attempt to formalise the Easterlin hypothesis in a simulation model and test its plausibility.
The Easterlin Hypothesis, developed by economist Richard Easterlin, purports to describe a mechanism whereby the fertility decisions of a particular cohort of individuals are linked to population level conditions that held sway when they were born The empirical support for the theory is quite strong for the certain periods in the history of the United States, but elsewhere it is circumstantial and patchy. A simulation model may allows us to test under what conditions it may hold and not hold, and also might help inform more general theory building.

Modelling the morphodynamic evolution of the Ganges-Brahmaputra-Meghna (GBM) Delta over centennial time scales

Stephen Darby (Investigator), Balaji Angamuthu

Around 0.5 Billion people live in deltaic environments where they are threatened by flooding and land loss frequently. Yet, our understanding of the threats posed by land dynamic process remains limited. In this work, we try to address this issue through a land dynamic simulation of the largest and most populated of all the deltas, the GBM Delta, using the CFD software Delft3D for a range of climate change and management scenarios. The results provide new insight into the factors controlling past morphodynamics that, in turn, are helpful when assessing the possible trajectories of future evolution.

Network Analysis of Roman Transport Routes in the Imperial Roman Mediterranean

David Potts

This research is designed to explore the nature of the relationships between Portus, Rome, and other selected ports in the Mediterranean and to establish patterns and the changing nature of trading networks derived from the distribution of known Roman artefacts.

OCCASION: Overcoming Capacity Constraints - A Simulation Integrated with Optimisation for Nodes

Tolga Bektas (Investigator)

OCCASION is a collaboration between TRG and the Schools of Mathematics and Management. The project's objective is to identify and investigate innovative methods of increasing the capacity of nodes (i.e. junctions and stations) on the railway network, without substantial investment in additional infrastructure. To this end, a state-of-the-art review of recent and ongoing work in this area will be conducted, followed by the development of tools to (i) assess existing levels of capacity utilisation at nodes, and (ii) investigate options for re-routeing and re-scheduling trains, with a view to reducing capacity utilisation levels. These tools will be used in combination to develop solutions delivering reduced levels of capacity utilisation, and thus increases in capacity and/or service reliability. Incremental changes to existing railway technologies (e.g. improved points) and operating practice (e.g. relaxations of the Rules of the Plan) will be investigated, as will concepts from other modes (e.g. road and air transport) and sectors (e.g. production scheduling).

Operational Simulation of the Solent Search-and-Rescue environment

James Scanlan, Kenji Takeda, Hans Fangohr (Investigators), Ben Schumann

This project aims to identify useful metrics for a proposed Search-and-Rescue UAV and test it virtually in a realistic environment.

Optimisation of Acoustic Systems for Perceived Sound Quality

Jordan Cheer (Investigator), Daniel Wallace

Acoustic systems have traditionally been optimised on the basis of minimising an objective acoustic measure, such as sound pressure level. The project investigates the use of subjective measures of sound quality, such as "loudness", "harshness" etc. in optimisation algorithms.

Origins of Evolvability

Richard Watson, Markus Brede (Investigators), William Hurndall

This project examined the putative evolvability of a Lipid World model of fissioning micelles. It was demonstrated that the model lacked evlovability due to poor heritability. Explicit structure for micelles was introduced along with a spatially localised form of catalysis which increased the strength of selection as coupling between potential chemical units of heredity were reduced.

Population24/7: space-time specific population surface modelling

Samantha Cockings, David Martin, Samuel Leung (Investigators)

Project funded by Economic and Social Research Council to compute time-specific geographical representations of population distribution.

Predicting Available Energy in Energy Harvesting Wireless Sensor Networks

Geoff Merrett (Investigator), Davide Zilli

Is it possible to predict how much energy a sun-light or wind powered wireless sensor node can harvest and tune its sensing pattern accordingly?

Reforging the Wedding Ring: Exploring a Semi-Artificial Model of Population for the United Kingdom with Gaussian process emulators

Jason Hilton

Note: Jakub Bijak from Social Science is the lead author on this project, which is forthcoming in Demographic Research (http://www.demographic-research.org/)
Co-Authors: Eric Silverman, Viet Dung Cao

We extend the „Wedding Ring? agent-based model of marriage formation to include some empirical information on the natural population change for the United Kingdom together with behavioural explanations that drive the observed nuptiality trends.

Replication of Sayama Group Decision Model

Jason Noble (Investigator), Jonathan Gray

Replication of a model of group decision making from Sayama et al. (2011), with a revised methodology that alters a conclusion from the original paper.

Respiratory mask modeling

Jacques Ernes

Abaqus modelling of repiratory masks, bioengineering, Health sciences

Sample tracking in whole-exome sequencing projects

Andrew Collins, Sarah Ennis (Investigators), Reuben Pengelly

Whole-exome sequencing is entering clinical use for genetic investigations, and it is therefore essential that robust quality control is utilised. As such we designed and validated a tool to allow for unambiguous tying of patient data to a patient, to identify, and thus prevent errors such as the switching of samples during processing.

SAVE: Solent Achieving Value through Efficiency

Patrick James, Ben Anderson (Investigators), Luke Blunden

Analysis of 15 minute electricity consumption and 10 second instantaneous power data from 4,000+ households in the Solent region collected over 3 years of a randomised control trial study.

Scalability of Energy Efficient Routing Algorithms in Wireless Sensor Networks

Geoff Merrett (Investigator), Davide Zilli

This project compares two broad classes of routing algorithms for Wireless Sensor Networks, message flooding and single path, by means of a simulation model. In particular, we want to understand how the two scale in terms of energy efficiency on large networks of sensors.

Self Interest & the Evolutionary Optimisation of Adaptive Trading Agents for Continuous Double Auctions

Frank McGroarty, Enrico Gerding (Investigators), Ash Booth

One cannot escape the recent crises in economics and the lack of understanding of financial markets that has been highlighted by them. Improvements to current market models are already being made and a realisation of the power of agent based modelling in such models is evident. In this project we seek to explore an existing model by Cliff of trader behaviour in continuous double auctions. We investigate the strategies that arise in such auctions when trader parameters are evolved with intent to maximise personal profit. Results show different trading strategies to those evolved by Cliff and explanations are given with regards to the self-interest.

Self Organized Network Routing using Quantum Evolutionary Methods

Lajos Hanzo (Investigator), Dimitrios Alanis

Self Organized Networks (SON) may consist of a large number of nodes, which could be fully interconnected. Optimizing its performance satisfying various Quality of Service (QoS) requirements is a quite complex procedure and the optimization problem belongs to the family of the Travelling Salesman Problems (TSP) which has been proven to be NP-hard as the number of nodes increases. In this project, various suboptimal methods are used in order to tackle this multi-objective optimization problem; in particular, the Ant Colony Optimization (ACO) and its quantum inspired counterpart (QACO) are being employed in order to reduce complexity.

Separation of timescales in models of complex networks

Seth Bullock (Investigator), Elisabeth zu-Erbach-Schoenberg, Connor McCabe

In many real-world systems several processes act on the system state. The way these processes interact can have implications for the resulting system state. We investigate how separation of the timescales of two processes influences the system's equilibrium state.

Simulating Household Decision Making in Rural Malawi

James Dyke, Kate Schreckenberg (Investigators), Samantha Dobbie

A scoping exercise to determine whether data collection tools of the social sciences can be used effectively in the construction of empirical ABM. Focus fell upon simulating drought coping strategies of Malawian smallholders. Model implementation enabled inferences to be made concerning the impact of drought and input subsidies upon smallholder food security.

Simulating Human Expansion in the Early Pleistocene

Seth Bullock, Fraser Sturt (Investigators), Iza Romanowska

Using Agent-based modelling to investigate the first human dispersal almost 2 million years ago.

Simulating Hydro-geomorphic Changes in European Climate Hotspots

John Dearing (Investigator), Ying Wang

This project will simulate the behaviour of hydro-geomorphological processes in a fluvial system over decadal timescales is an important basis for research on catchment environmental management, especially with regards climate changes and human impacts on fluvial system.

Simulating Sleeping Sickness: a two-host agent-based model

Jason Noble, Peter Atkinson (Investigators), Simon Alderton

Sleeping sickness is a vector-borne, parastic disease which affects millions of people across 36 sub-Saharan African countries. Using agent-based models, we aim to gain a greater understanding of the interactions between the tsetse fly vector and both animal and human hosts.

Building an accurate representation will allow the testing of local interventation scenarios including the closing of watering holes, and the selective spraying of cattle with insecticides.

Simulation of Parking Choice Behaviour

Ben Waterson, Hans Fangohr (Investigators), James Snowdon

Exploring how psychological models of individual parking search behaviours can be combined into an accurate simulation of vehicle flows, allowing for assessment of the impact on searching traffic of different demand/ supply ratios, different driver population characteristics and different charging regimes.

Spatial Mobility in the Formation of Agent-Based Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into the effect of spatial mobility on endogenous economic network formation.

Spatially Embedded Complex Systems Engineering

Seth Bullock (Investigator)

SECSE brought together an interdisciplinary team of scientists working on an ambitious three-and-a-half year project titled. The research cluster spanned neuroscience, artificial intelligence, geography, and complex systems in an attempt to understand the role of spatial organization and spatial processes in complex networks within the domains of neural control, geo-information systems and distributed IT systems such as those implicated in air-traffic control.

TEDx: Closing the Loop: Entropy Accounting for a Sustainable World

Stuart Bartlett (Investigator)

This is a TEDx talk that I gave on some ideas I've had about the large-scale thermodynamic organisation of life on Earth. While these ideas probably aren't new, I believe they can teach us something about the way in which we think about energy and the 'consumption' of goods and energy.

The Endogenous Formation of Economic Networks

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

An investigation into endogenous network formation using a simple agent-based approach.

The Role of Information in Price Discovery

Antonella Ianni, Seth Bullock (Investigators), Camillia Zedan

The recent economic crisis has highlighted a continued vulnerability and lack of understanding in the financial markets. In order to overcome this, many believe that current market models must be improved. Recently, a trend towards agent-based modelling has emerged. Viewing the economy as a complex system is beginning to be seen as key to explaining certain market characteristics that were originally considered anomalies.

One of the fundamental assumptions in economics is that of information efficiency: that the price of a stock reflects its worth, that all possible information about a security is publicly known, and that any changes to price take place instantaneously. In reality, however, this is not the case.

This project considers the use of agents in modelling economic systems and demonstrates the effect of information levels on price discovery using a simple market simulation.

The Role of the Biota in the Carpenter Model on Lake Eutrophication

James Dyke (Investigator), Alexandra Diem

The Carpenter model is a useful and simple model to predict the eutrophication of shallow lakes via phosphorus input. This project aimed at resolving the function of the biota, which play a major role in the phosphorus dynamics, but are so far only implicitly modelled, and extending the model to explicitly represent them.

The Social-cognitive Niche: An Exploration of the Co-evolutionary Relationship between Human Mind and language, with a Particular Focus of the Self-organisational properties of the Emergence of Symbolic Representation.

Jason Noble, Glyn Hicks (Investigators), Lewys Brace

This work explored the relationship between the origin and subsequent evolution of the human mind and language; a relationship that is believed to be symbiotic in nature. This piece aimed to achieve two objectives. Firstly, it set out a theoretical framework, using the principles of complexity theory and self-organisation, which attempts to explain this relationship from a holistic perspective.

Secondly, it presented an agent-based model of a vervet monkey social group, which sought to investigate the variables that were perceived to underpin the emergence of symbolic representation within a population of language users.

The belief here was that, by understanding the influence of these variables, one would be able to better understand the genesis of the aforementioned relationship.

Traveling and movement during European Late Prehistory

Patricia Murrieta Flores

This project has as main purpose to investigate through spatial analysis and computational modelling the variables and factors that influenced how humans traveled during prehistoric times.
One of the principal objectives will be to clarify the role that certain landscape elements (i.e megalithic monuments) played in terrestrial navigation and territorial definition.

This project is supported by CONACYT (Mexico) as a doctoral research by Patricia Murrieta-Flores under the supervision of Dr. David Wheatley (University of Southampton) and Dr. Leonardo Garcia Sanjuan (University of Seville, Spain). It also counts with the collaboration of Dr. Dimitrij Mlekuz (Gent University, Belgium).

Using computer intensive methods to produce small area estimates of poverty

Nikolaos Tzavidis (Investigator), Steve Donbavand

By using computer intensive methods this work compares, and suggests improvements, to existing methods for estimating poverty levels. These poverty estimates are used to produce maps which in turn help to target government policies.

Wind direction effects on urban flows

Zheng-Tong Xie, Ian Castro (Investigators), Jean Claus

Numerical simulations of turbulent air flow are conducted on Iridis to investigate the effects of different wind directions on the flow within and above an urban-like canopy.

µ-VIS Computed Tomography Centre

Ian Sinclair, Richard Boardman, Dmitry Grinev, Philipp Thurner, Simon Cox, Jeremy Frey, Mark Spearing, Kenji Takeda (Investigators)

A dedicated centre for computed tomography (CT) at Southampton, providing complete support for 3D imaging science, serving Engineering, Biomedical, Environmental and Archaeological Sciences. The centre encompasses five complementary scanning systems supporting resolutions down to 200nm and imaging volumes in excess of one metre: from a matchstick to a tree trunk, from an ant's wing to a gas turbine blade.