Overview of Research Interests
My interests lie the area of Biologically Inspired Computing, in particular Artificial Immune Systems (AIS). I undertake research in three main areas: optimisation, self-organising and self-adaptive systems, and understanding biological systems.
- Hyper-heuristics as a practical method of solving optimisation problems encountered in the real world, e.g packing, scheduling and routing
- Use of optimisation techniques to minimise carbon emissions and in low-carbon technologies and renewable energy sector
- Optimisation systems that learn from experience and self-improve over time
Understanding biological systems
- How can ideas from complex biological systems effectively be transferred to algorithms for use in engineered systems, through a process of modelling and abstraction ?
- Understanding the role of complex networks in biological systems - in particular, understanding through modelling and simulation how the topology of a biological network ultimately influences the
functionality of that network.
- Fundamentals of Collective, Adaptive Systems
Self-adaptive and Self-organising Systems
- Applying immunological and other biological inspiration to building self-maintaining,
adaptive, autonomous, distributed systems which have
to continuously operate inside some kind of viability zone
- Learning in autonomous systems e.g evolutionary robotics
- Adaptation and learning in distributed systems such as wireless sensor networks
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For latest news and events, please see the project webpage here Awareness is a Coordination Action (CA), supporting research under the FP7: FET Proactive Intiative:Self-Awareness in Autonomic Systems (Awareness). Awareness provide a supportive environment for research into self-awareness in...
Starting on 1/1/2013, this project aims to improve the current state of the art in developing optimisation tools which are relevant and acceptable to industry. This will be achieved by addressing industrial current concerns regarding the ability of academic optimisation techniques to deal...
FOCAS is a coordination action in the area of collective adaptive systems. It provides increased visibility to the research carried out by projects funded by the FOCAS FET Proactive Initiative and others in research fields related to collective adaptive systems.
PhD Project Involvement
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Towards a noveI approach to greener software services in the cloud.
Immune based anomaly detection in wireless sensor networks. The topic Addresses the development of novel secrity echanisms for mobile ad hoc networks, inspired by mechanisms apparent in the biological immune system.
Interactivity in collaborative room environments.
A hyper heuristic approach to optimisation. Hyper-heuristics (HH) have been described as methodologies that aim to offer “good enough -soon enough - cheap enough” solutions to real world problems.
Exploiting narrative hierarchies within computer games. One of the challenges of artificial intelligence in computer games is the effective use of learning to either automate the creation of intelligent agents for the release of a game, or to allow agents...
Bio-inspired computing for optimisation/self-organising systems.
Hart, E. (2013). Generating Single and Multiple Cooperative Heuristics for the One Dimensional Bin Packing Problem Using a Single Node Genetic Programming Island Model. In: Alba, E.,
al, e. (Eds.) Proceedgs of GECCO 2013, , () ( ed.). (pp. ). : . ACM SIGEVO.
Hart, E. (2013). Incorporating Emissions Models within a Multi-Objective Vehicle Routing Problem. In: (Ed.) To appear in: GECCO'13 Companion, , () ( ed.). (pp. ). : . .
Hart, E. (2013). Using Graphical Information Systems to improve vehicle routing problem instances. In: (Ed.) GECCO'13 Companion, , () ( ed.). (pp. ). : . .
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