The field of Artificial Immune Systems (AIS) is a new and exciting area of research whose implications for the design and implementation of systems in the future are manifold. This is not limited to the obvious virus detection in computer systems, but can extend from fault-tolerant hardware design to adaptive systems. The group undertakes work in both theoretical and practical aspects of artificial immune systems. We work with an interdisciplinary perspective, developing computational models of immunology that help both to drive immunological experimentation and to inspire the design of new engineering solutions. Applications of our work include swarm robotics, fault prediction in self-service devices, the design of self-regulating electronic devices and long-term autonomy for robotic systems.
An Extensible Architecture for Homeostasis in Electronic Systems
Members: Andy Greensted, Nick Owens, Jon Timmis, Andy Tyrrell
Imagine an engineered system that can predict, or be aware of, imminent threats upon its specified operation. Then, based on this prediction, the system can alter its operation or configuration to circumvent the effects of the threat. The focus of the research is on one of the most impressive abilities of living organisms: their ability to ensure a reasonably stable internal state despite wildly changing external environmental factors. The project aim is to develop an architecture that endows electronic systems with the ability to self-regulate their physical and operational state within highly dynamic environments.
Members: Pitiwut Teerakittikul, Gianluca Tempesti and Andy Tyrrell
Adaptability is an essential ability of autonomous robots working in real-world human-hazardous environments. These kinds of environments are dynamic and full of unexpected circumstances caused by environmental changes. In fact, changes can happen in both internal (e.g. faults occur on robot’s components or a reduction of robot’s power) and external systems (e.g. changes of terrain characteristics or roughness) of the robots. The main purpose of this research is to utilize artificial hormones in order to provide adaptability for an autonomous 4-wheel robot in such a way that it can cope with both internal and external environmental changes.
ARTIST: A Network for Artificial Immune Systems
Members: Jon Timmis, Andy Tyrrell
The field of Artificial Immune Systems (AIS) is a new and exciting area of research, whose implications to the design and implementations of systems in the future are manifold. This is not limited to the obvious virus detection in computer systems, but could extend from fault-tolerant hardware design to machine learning. However, to allow this new area to develop and for the UK to continue to lead the world in such activities, a more structured approach is needed to co-ordinate and support researchers in this area. This network is designed to help bolster these researchers in the UK, stimulate and extend the community of AIS practitioners within the UK, and provide the necessary infrastructure and financial support for them to pursue further interactions between themselves and international collaborators in order to drive forward this area of research.
BIASPROFS: Artificial Immune Systems for Bioinformatics
Members: Jon Timmis
BIASPROFS is a joint computing and biology research project with the aim of producing novel algorithms inspired by immunology for predicting the functions of GPCRs (G-protein-coupled receptors), an important kind of protein which interacts with many medical drugs. We are developing computational models of immunological processes that will ultimately lead to the development of novel immune inspired algorithms for the classification of GPCRs. This is in collaboration with University of Kent and University of Oxford (Jenner Institute for Vaccine Research).
Members: Jon Timmis, Andy Tyrrell, Mark Read, James Hilder
CoCoRo is an ambitious project which aims at creating a swarm of interacting, cognitive, autonomous robots. We will develop a swarm of autonomous underwater vehicles (AUVs) that are able to interact with each other and which can balance tasks (interactions between/within swarms). These tasks are: ecological monitoring, searching, maintaining, exploring and harvesting resources in underwater habitats. The swarm will maintain swarm integrity under conditions of dynamically changing environments and will therefore require robustness and flexibility. This will be achieved by letting the AUVs interact with each other and exchange information, resulting in a cognitive system that is aware of its environment, of local individual goals and threats and of global swarm-level goals and threats.
Members: Jon Timmis, Andy Tyrrell
Our project will build capacity in generic modelling tools and simulation techniques for complex systems, to support the modelling, analysis and prediction of complex systems, and to help design and validate complex systems. Drawing on our state-of-the-art expertise in many aspects of computer systems engineering, we will develop CoSMoS, a modelling and simulation process and infrastructure specifically designed to allow complex systems to be explored, analysed, and designed within a uniform framework.
Immune System Based Fraud and Fault Sensor System
Members: Jon Timmis, Adam Knowles and Rogerio De Lemos (Kent)
There is currently increased public awareness regarding the potential for fraud in financial services, especially with respect to well-publicised ATM fraud attacks. This has lead to an increased requirement for additional sensing in the ATM to detect these types of attack. This requires intelligence to be built into the system to allow more efficient processing of the new complex data that is available in the ATM. The intelligence uses “sensor fusion” to amalgamate the data and process it to produce more accurate alarm messages to the ATM network control system. This project aims to provide the intelligence for the processing of the sensor data allowing the raw data to be converting into more accurate and complete alarm messages that can be passed into the management and fraud detection systems. This project is in collaboration with NCR (http://www.ncr.com) and Rogerio De Lemos of the Computing Laboratory at The University of Kent (http://www.cs.kent.ac.uk/people/staff/rdl).
Members: Jon Timmis, Andy Tyrrell, James Hilder, Nick Owens
The Robotic Sniffer Dog project is a project funded by DSTL which attempts to improve the accuracy and reliability of automatic chemical agent detection using a robotic platform. The project was initial funded due to the success of the Receptor Density Algorithm (RDA), an immune-inspired algorithm developed by Dr. Nick Owens as part of his PhD research project, at detecting anomalies within a Proton-Transfer Reaction Mass Spectrometry data-set in a competition organised by DSTL at the ICARIS 2009 Conference. The RDA is inspired by the signalling mechansims found within T-cells, and is developed from models of the immunological T-cell and the T-cell recport's ability to contribute to T-cell discrimination.
Members: Jon Timmis, Andy Tyrrell, Maizura Mokhtar, Ran Bi
This is a collaborative European project funded by the EU FET Proactive Initiative on Pervasive Adaptation. The main focus of this project is to investigate and develop novel principles of adaptation and evolution for symbiotic multi-robot organisms based on bio-inspired approaches and modern computing paradigms.