Complexity, Criticality, and Computation (C3) International Biannual Symposium
Thursday 26 - Friday 27 November 2015
Organised by Charles Perkins Centre and Research Cluster for Complex Systems
Complex systems is a new approach to science, engineering, health and management that studies how relationships between parts give rise to the collective emergent behaviours of the entire system, and how the system interacts with its environment.
What makes a system ‘complex’? A system can be thought of as complex if its dynamics cannot be easily predicted, or explained, as a linear summation of the individual dynamics of its components. In other words, the many constituent microscopic parts bring about macroscopic phenomena that cannot be understood by considering a single part alone (‘the whole is more than the sum of the parts’). There is a growing awareness that complexity is strongly related to criticality: the behaviour of dynamical spatiotemporal systems at an order/disorder phase transition where scale invariance prevails.
Complex systems can also be viewed as distributed information-processing systems, particularly in the domains of computational neuroscience, health, bioinformatics, systems biology and artificial life. Consciousness emerging from neuronal activity and interactions, cell behaviour resultant from gene regulatory networks and swarming behaviour are all examples of global system behaviour emerging as a result of the local interactions of the individuals (neurons, genes, animals). Can these interactions be seen as a generic computational process? This question shapes the third component of our symposium, linking computation to complexity and criticality.
When: 9am - 5pm, 26 - 27 November
Where: Charles Perkins Centre Auditorium
Download the International Biannual Symposium program
- Prof. Guy Theraulaz, Director of Research Centre on Animal Cognition, Université
Paul Sabatier, Toulouse, France
Research interests: Swarm Intelligence in natural and artificial systems, Self-organization in biological systems, Collective Behaviors and Collective Intelligence in animal and human societies, Computational and Systems Biology
- Dr. Francesco Caravelli, Invenia Labs, Cambridge, UK
Research interests: Physics in a broad sense, classical and quantum, and in complexity theory. Complex networks, cellular automata, machine learning, agent-based modelling, complex networks and their applications to engineering and economics.
- Dr. Markus Brede, University of Southampton, UK
Research interests: artificial life, computational economics, evolutionary game theory, individual-based modelling, network science, self-organisation, socio-economic systems, spatial networks.
- Dr. David Balduzzi, University of Wellington, New Zealand
Research interests: machine learning, computational neuroscience, information theory, statistical learning theory
- Professor Leonid Churilov, Florey Institute of Neuroscience and Mental Health, Australia
Research interests: statistical modelling, research and design analysis, decision support in clinical and health care systems, biostatistics, imaging
- Dr. Jerome Buhl, Adelaide University, Australia
Research interests: Experimental and theoretical studies of insect collective behaviour and its application to agriculture and pest control. Current focuses on locust hopper bands, ant and termite colonies.
- Prof. Pip Pattison, University of Sydney, Australia
Research interests: development and application of mathematical and statistical models for social networks and network processes. The work has broad application, from tracking the spread of infectious diseases to following the recovery of communities after the 2009 Victorian bushfires.
- Prof. Terry Bossomaier, Charles Sturt University, Australia
Research interests: Theory and applications of complex theory; agent based modelling;
cognitive networks; simulation and visualisation; econophysics.
- Prof. Robert Marks, University of NSW, Australia
Research interests: Using simulation and machine learning in exploring oligopolistic behaviour and decision making under risk; validation of simulation models based on historical data
- Prof. Peter Robinson, University of Sydney, Australia
Research interests: Member of the Brain Dynamics Group within the Complex Systems Group. The Brain Dynamics group is an interdisciplinary team with backgrounds in physics, engineering, mathematics, IT, psychology, physiology, medicine, and other areas. Its aim is to understand the connections between physiology and stimuli, on one hand, and resulting brain activity and experimental data, on the other.
- Prof. Hugh Durrant-Whyte, University of Sydney, Australia
Research interests: Field robotics, in particular the fields of sensor data fusion and of autonomous vehicle navigation. Pioneered decentralized data fusion which has led, inter alia, to the world’s first demonstration of a cooperative, multi-platform fleet of unmanned aircraft for search and surveillance.
- Prof. Mikhail Prokopenko, University of Sydney, Australia
Research interests: analysis, modelling and predictions of critical phenomena, aimed to improve robustness and resilience in a range of complex self-organising systems during technological, sociological and socioeconomic crises. The approach is motivated by the search for a fundamental theory of non-equilibrium information thermodynamics in systems capable of complex computation.
- Dr Virgil Griffith, Chief Technical Officer, Backbone Telecommunications, Singapore
Research interests: information theory, synergy, consciousness, irreducibility.
Learn about our Complexity, Criticality and Computation (C3) Research Camp