The ARC Centre for Complex Systems (ACCS) conducted a world-class research program on the science and engineering of complex systems.
The Centre was a partnership between
- The University of Queensland (Brisbane)
- Monash University (Melbourne),
- Griffith University (Brisbane), and the
- UNSW@ADFA (Canberra)
International collaborating organisations included France’s Centre National de la Research Scientifique and the Indian Institute of Technology. Collaborating investigators were drawn from other Australian and overseas research organisations, including Boeing, CSIRO and the Santa Fe Institute.
The ACCS was established in 2004 as part of the the Australian Research Council's Centre of Excellence program. It was funded until mid-2009. The results achieved by the Centre over the five years of its existence, including theory, methods and tools, have laid the foundations for significant follow-on applied research projects in collaboration with industry (details of these projects are in the 2008 Annual Report, linked to below). In particular, the Centre's three core research programs in 2008 - air traffic managment, electricity networks and energy markets, and dependable computer-based systems - have all secured follow-on funding to apply their research outcomes in industry collaborations.
The Director, Peter Lindsay, and 12 Chief Investigators led a team of researchers, collaborators and students in their research into the science and engineering of complex systems. See the list of ACCS people.
The ACCS was interdisciplinary, involving leading researchers from a range of disciplines including:
- systems and software engineering,
- human factors,
- computational mathematics and statistics, and
- relevant application domains including economics, bioscience, and air-traffic control.
The strategic direction of the Centre was guided by the ACCS Advisory Board.
The goal of the Centre was to develop a deeper understanding of fundamental phenomena in complex systems such as how macro-level system properties and behaviours emerge from relatively simple micro-level interactions, what mechanisms enable complex systems to self-organise, and how complex systems can be managed and controlled.
- The growth in air traffic, ACCS Director, Peter Lindsay, is interviewed by Robin Williams for ABC Radio's Science Show, July 7 2007
Use of modelling to study non-linear systems: 2 examples (with video) ACCS Director, Peter Lindsay
gave a 1 hour talk to the
University of York Centre for Complex Systems Analysis on 28th November 2008.
This talk outlined two areas of application for models of non-linear systems: genetic regulatory networks, whereby sets of genes work together in networks to regulate cell growth in biological organisms, determining for example what kinds of cells will be produced when cells split and where the new cells will be positioned; and patient flow through a hospital Emergency Dept, where small fluctuations in arrivals can have unexpected effects.
- 2008 Annual Report (pdf, 1.3M)
- 2007 Annual Report (pdf, 1.4M)
- 2006 Annual Report (pdf, 0.7M)
- 2005 Annual Report (pdf, 2.8M)
- 2004 Annual Report (pdf, 1M)
- 2003 Annual Report (pdf, 0.3M)
ACCS in the media - listing and links to some media coverage of Centre research
ACCS brochure - provides further general information on the Centre and its research.
VLAB, Monash University's Artificial Life Virtual Lab presents simulations to help you understand how complex organisation and behaviour emerges in living systems.
A series of demonstrations of some aspects of ACCS research:
- Building dependable systems (Behavior Trees)
- Modelling from sequence to gene regulatory network to phenotype
- Checking fault tolerance in safety and security-critical systems
- Modelling neurosphere formation with neurosphere lab
ACCS Technical Reports
- Feasibility study on implementing the SafeHCI model in Micro Saint
- Practical software engineering techniques for regulatory models in biology
- Modelling globular cell colony growth
- Simulation of Air Traffic Controllers' behaviour using the operator choice model
- Control and constraint: Cross centre insights from modelling cellular morphogenesis
- A semantics for Behavior Trees
- Interactively exploring distributed computational models of biology