Agent-based computing, with its emphasis on autonomous and flexible problem solvers, is widely regarded as the foundation for many complex systems. Our work in this area is concerned with both the theory and the practice of the field. In particular, we focus on interactions such as cooperation, coordination and negotiation and how they interplay with the sensing, reasoning and acting capabilities of the individual actors.
Applying and extending network theory to deal with the large-scale and topologically complex networks found in domains such as biology, computing, geography and knowledge representation. Example topics: constraints on networks due to spatial layout, integration of multiple interacting networks, network sampling, network structure in markets, ontology networks, social networks.
Computational economics is a core part of the AIC research agenda and applies game-theoretic and market-based economic principles to the design and understanding of multi-agent systems. Research areas include algorithmic game theory, coalition formation, mechanism design, automated negotiation, social choice, and agent-based computational economics. Applications include sponsored search, cloud computing, the smart grid, e-business, and disaster management.
Focussing on the science and practise of building system that can operate with minimal human intervention in dynamic and uncertain environments where information and control is decentralised.
Understanding the underlying algorithmic principles of biological systems, via the application of modelling techniques developed in artificial intelligence to problems in ecology and evolution. Example topics: the major transitions in evolution, the evolution of sex, symbiosis and symbiogenesis, ecosystem selection in biofilms, collective building behaviour in insects, the evolution of signalling and communication, social learning behaviour, mimicry, the epistemological status of evolutionary simulation models.
Human Computer Interaction (HCI) research focuses on how people interact with technology and on the design of novel interfaces and interaction techniques. In particular our interests are in systems and strategies to support innovation and creativity, and help users in making sense of large amounts of data. To this end, we create and evaluate prototypes that range from tangible and mobile interfaces to Web applications.
Our research in Informed Matter focuses on integrating information processing into physical and chemical systems to enable the formation of complex structure and functionality. The overall aim is to facilitate a step-change in the complexity of synthetic materials and thus narrow the gap between the intricate material organisation found in the biological world and what is available in the present engineering tool-kit. AIC activities in Informed Matter range from molecular to macroscopic scale and include molecular computing, self-assembly, and bio-hybrid devices.