Complex systems are ubiquitous in today’s world and they experience serious issues caused by emergent behavior, self-organization, and cooperation among their entities. Emergence becomes a distinguishing system feature as system complexity grows with the number of components, interactions and connectivity. Example of emergent behaviors include the flocking of birds, traffic jams, ant colonies, biological life, hubs in social networks, competition in energy power markets, smart grids, and smart cities among others. Despite significant research interest in recent years, there is a lack of formal methods to understand, identify, and predict the behavior of complex systems, especially as systems grow in size, inter-connection between components, the number of component attributes and their geographical distribution.
This project looks at practical approaches for the computer-aided analysis of current complex systems, with a focus on obtaining insight into their behavior.
Project leader: Dr Claudia Szabo.
Claudia Szabo, the Complex Systems project leader will be pitching research ideas during the Land Forces 2016 conference. Come and find her to discuss ways of best modeling human interactions (both in person and online) in areas of conflict, to best identify emerging unwanted behaviors! The work builds on the group’s modeling of complex systems […]
Scott Bourne’s PhD thesis was recognised by Dean’s Commendation for Doctoral Thesis Excellence. Co-supervised by Prof. Michael Sheng and Dr Claudia Szabo, Scott’s PhD project focuses on developing novel solutions on formal validation of service-based business processes based on model checking techniques. The result has the potential to be applied in mission-critical applications (e.g., defence) […]
Self-organisation is one of the key properties of complex systems yet automated tools to identify it have yet to be applied to systems other than toy models such as the Game of Life. Lachlan’s work is looking at implementing system complexity, Chan’s interaction metric, limited bandwidth recognition, de-centralised emergence detection and multi-scale Shannon entropy. His experiments […]
Lachlan’s paper proposing a modeling language for complex adaptive systems has been accepted to WSC 2016! Abstract: Complex adaptive systems (CAS) are ubiquitous across many domains, such as social networks, supply chains, and smart cities. Currently, the modeling and analysis of CAS relies on adapting techniques used for multi-agent simulation, an approach which lacks several features […]
Lachlan Birdsey’s paper on modeling and visualizing the emergence of knowledge topics on Twitter has won the Best Applied Paper Award at WSC 2015. Congratulations Lachlan! Title: Twitter Knows: Understanding The Emergence Of Topics In Social Networks Abstract: Social networks such as Twitter and Facebook are important and widely used communication environments that exhibit scale, complexity, node interaction, […]
The Australian Genome Research Facility awards $15,000 for the project Mega barcoding: Next Generation ‘de novo’ barcoding for health, agriculture and environment, whose main aim is to to broaden the coverage of existing plant barcode markers to include subsidiary markers to improve diagnostic resolution. Well done, team!
Lachlan Birdsey joins CDIT as a PhD student working on the modeling and analysis of complex adaptive systems. Welcome Lachlan!
Jayden Barnes and Jacob McIver join CDIT to work on the Fiddler Crab project. Welcome Jayden and Jacob!!
The University of Adelaide awards $28,000 to the project: Fiddler on the Cloud: Understanding the Evolution and Diversity of Form and Function in Crustaceans. This project partners the School of Computer Science and the School of Biological Sciences to investigate the effects of environmental changes on the species diversity by analysing the evolution of biological shapes and […]
Lachlan Birdsey’s paper on modeling and visualizing the emergence of knowledge topics on Twitter has been accepted for publication in WSC 2015. Congratulations Lachlan! Title: Twitter Knows: Understanding The Emergence Of Topics In Social Networks Abstract: Social networks such as Twitter and Facebook are important and widely used communication environments that exhibit scale, complexity, node interaction, and […]