About Fabio Boschetti

Emergence Workshop

Multi-disciplinary Perspectives on Emergence in Complex Systems

12-14 May 2005, Canberra

CSIRO Sustainable Ecosystems, Gungahlin Homestead

Introduction.. This workshop is a component of the 'Emergence Interaction Task', planned as a part of the CSIRO Complex Systems Science initiative in early 2004. It follows the introductory discussions which were held during the last CSS meeting in Coffs Harbor (2004). During that meeting it was decided that

9.10 Cosma Shalizi , "Emergence, Levels of Description, and the Complexity of Prediction"

10.20 Mikhail Prokopenko , "Towards an "ageless" aerospace vehicle: design vs self-organization"

11.20 Daniel Polani , "Evolution of Sensors and the Perception-Action Loop "

2pm Dave Winkler , "Understanding and Modelling Emergence at the Chemistry:Biology Interface"

Dr. Cosma Shalizi , "Emergence, Levels of Description, and the Complexity of Prediction"

Abstract : Emergence is a relationship between two levels of description of a single system, but what kind of relationship, exactly? One common answer is that higher-level phenomena emerge from lower-level ones if the former cannot be predicted from the latter. In this talk, I will try to convince you that this answer cannot be made precise in any scientifically useful way. I will then present an alternative, which is that higher-level phenomena are emergent when they are easier to predict than lower-level ones. Recent work on the information-theoretic complexity of prediction in dynamical systems lets this idea be formulated precisely, and I'll present examples of its application to the emergence of thermodynamics from statistical mechanics, and to aspects of pattern formation in cellular automata.

Biographical Notes : Dr. Shalizi is a post-doctoral fellow at the Center for the Study of Complex Systems at the University of Michigan . He obtained his Ph.D. in physics from the University of Wisconsin-Madison in 2001, and worked at the Santa Fe Institute from 1998 to 2002. His research focuses on information-theoretic methods of nonlinear prediction, machine learning for dynamical systems, and quantitative measures of complexity and self-organization. He will be joining the statistics department of Carnegie-Mellon University in June as a visiting assistant professor.

Dr Mikhail Prokopenko , "Towards an "ageless" aerospace vehicle: design vs self-organization"

Abstract : Robust or "ageless" aerospace vehicles are expected to be capable of structural self-assessment and repair. The research results presented in this talk were obtained as part of the joint CSIRO-NASA Ageless Aerospace Vehicles project, involving an experimental test-bed system. The initial goal of the current AAV Concept Demonstrator is the detection and evaluation of high velocity impacts. This talk describes the underlying principles, methodology, preliminary results and lessons of simulating and developing a multi-agent sensor and communication network in a dynamic decentralized setting, motivated by a self-monitoring, self-repairing AAV. In particular, we investigate self-organization of robust impact boundaries enclosing critically damaged areas, formation of impact networks connecting survived nodes in presence of connectivity disruptions, self-organizing diagnostics, and possible shape replication strategies. The self-organizing patterns are shown to have distinct higher-order emergent properties, quantitatively measured with graph-theoretic and information-theoretic techniques. This allows us to clearly identify phase transitions, separating chaotic dynamics from ordered and robust patterns, and evolve some of the required configurations with genetic algorithms.

Biographical Notes : Mikhail Prokopenko is a senior research scientist at CSIRO ICT Centre, with a Ph.D. (Computer Science, Macquarie University, Australia), an M.A. (Economics, University of Missouri-Columbia, USA), and an M.S. (Applied Mathematics, Azerbaijan Oil and Chemistry Institute, USSR). His long-term research goal is design and control of complex self-organizing multi-agent systems, and an effective integration of real-time perception, reasoning and action in autonomous agents. His work has resulted in over 40 publications and patents. In June 2002, Mikhail Prokopenko received the JSAI (Japanese Society for Artificial Intelligence) award. Presently, Mikhail is coordinating the Multi-Agent Algorithms team within the CSIRO-NASA research project on Ageless Aerospace Vehicles.

Abstract : The principle of accessing new sensoric channels and to make use of the implicit information coded in these channels has been exploited in nature to a formidable degree. Olfactory, tactile, auditive and visual, but also electric and even magnetic senses have been realized in a vast multitude of variants, often utilizing organs not originally "intended" for the purpose they serve. At the same time, as already Darwin points out, it seems difficult to believe that an organ of such complexity as e.g. the eye "[...] could have been formed by natural selection [...]". Nevertheless photoreceptors of widely different degree of differentiation have evolved in at least forty independent lines of descent.

The study of sensor evolution has ramifications not just in biology but is of high relevance to the artificial design of adaptive sensomotoric and embodied devices. Moreover, recent research has uncovered deep connections between the evolution of sensor, principles guiding the structure of the perception-action loop and fundamental issues of the emergence of life and intelligence.

The talk will give an overview over particularly fascinating and illuminating examples of sensor development in nature, it will provide lessons learnt about artificial systems and, finally, it will cast a spotlight on some very recent advances in a quantitative theory of the field which shed not only light on existing processes, but provide explanatory, predictive and even constructive power.

Biographical Notes : Daniel Polani obtained his PhD in 1996 at the University of Mainz ( Germany ) on work about the Genetic Evolution of Self-Organizing Maps. In 1996-2000, he was a research fellow at the University of Mainz , and in 1997 a visiting researcher at the University of Texas in Austin . In 2000-2002 he worked at the Institute for Neuro- and Bioinformatics at the University of Luebeck ( Germany ). Since 2002, he is member of the Algorithms and Adaptive Systems Research Groups at the University of Hertfordshire , organizer of the EAL (Embodied Artificial Life) meetings and leader of the SEPIA (Sensor Evolution, Processing, Information and Actuation) group.

A central point of Daniel Polani's research is the modelling and understanding of complex and self-organizing and -adaptive systems. Since 1996, this research direction is incarnated in two research directions: the study of multiagent systems and of sensor evolution. In multiagent systems, he has done work in the RoboCup framework, on trading agent dynamics and on the emergence of social norms in agent societies. His research on sensor evolution ranges from the conditions driving the emergence of sensorics and their relation to biological systems to fundamental questions about the principles guiding their organisation and that of the perception-action loop. In addition, in his work he aims at the structuring of sensomotoric loops from first principles.

Daniel Polani is member of the RoboCup executive committee and reviewer for national and international research councils (e.g. UK , US, Germany , Netherlands ) as well as renowned international journals and member of a large number program committees.

Abstract : Emergence is everywhere in biology, from the development of an organism to its decline. At one end of the spectrum emergence is seen to affect biological molecules, their actions and interactions, while at the other we can study an affect on a whole individual or a population of individuals. For example, there is now considerable evidence that some diseases result from a chance event to produce a structural change in a normal cellular protein. This change appears to be then "transmitted" efficiently to the other normal cellular proteins such that a disease results. More convenient studies of emergence can be made in microbial systems where a range of diseases can be modeled. For example, drug resistance once considered to be due simply to a novel nucleotide change in a DNA sequence, can now be shown to have considerable complexity when techniques such reverse engineering and expression profiling are applied.

Biographical Notes : Ian Macreadie completed his Ph. D. in Tony Linnane's laboratory at Monash University in 1983. While there he identified mitochondrial genes of yeast that encoded subunits of H + -ATPase using early cloning and sequencing approaches, coupled with classical yeast genetics. He then continued with mitochondrial gene identification as a Post Doctoral Research Fellow with Ron Butow at the University of Texas Health Science Center at Dallas . There he identified a gene within the intron the 21S rRNA gene which encoded an endonuclease involved in transposition of the intron. In addition he worked on the var1 gene which was 90% A+T. In 1985 he was recruited by CSIRO where he currently serves as a principal research scientist. Over the past 20 years at CSIRO he has utilized his skills in yeast molecular biology for biotechnology and medical applications. Much of this included the development of yeast expression systems for various purposes including the production of a subunit vaccine that provided protection against infectious bursal disease virus, as well as various antigens for diagnostic use. Work on the analysis of the "pathogenic" proteins of HIV proteins Nef and Vpr in yeast indicated that yeast could be used as a model to decipher the functions of those viral proteins and to aid the design of novel inhibitors. Since 1997 Macreadie has focused on antimicrobials and drug resistance, but most recently on Alzheimer's disease modeling in yeast. The antifolate work has included the development of yeast models for sulfa drug resistance in Pneumocystis and Plasmodium in collaboration with Carol Sibley, Steven Meshnick, Worachart Sirawaraporn, Philippe Hauser, Janette Berglez, Onisha Patel and Peter Iliades. This has included the construction of various yeast strains lacking folate synthesis which has enabled considerable new understanding about folate utilisation. There is also a major focus on coupling structural knowledge with in silico docking to derive novel antimicrobials that will evade the development of drug resistance. Ian Macreadie is an Adjunct Professor of RMIT University and is a leader in the Australian yeast community. He is an author of 92 research publications.

Dr. Dave Winkler, "Understanding and Modelling Emergence at the Chemistry:Biology Interface"

Abstract : There is increasing awareness that many chemical and biological systems are 'complex', exhibiting behaviours and properties that emerge from the interaction of many components in the system. Such emergent properties often cannot be modelled using reductionist methods. Molecules are complex, adaptive systems formed when atoms are linked in various ways. They are nanodevices that can be designed and assembled under extremely precise control, using synthetic chemistry. Molecules are capable of exquisite modulation of complex biological systems, performing extremely useful functions in medicine and crop care and having a profound effect on complex populations of plants, animals and people. They have individual and group emergent properties and behaviours that are manifest in an almost infinite variety of materials and properties.

Our group applies ideas, concepts and methods of complex systems science and artificial intelligence to model emergent properties of molecules in chemical, biological, and medical contexts. Our work covers a range of applications, some of which are established and other nascent. We use agent-based methods, such as neural networks, to model emergent biological response properties. We employ genetic algorithms to evolve chemical libraries, using as fitness functions neural network-derived models. These libraries are focused - are designed to be enriched in molecules with desirable properties such as high potency, selectivity, and favourable ADMET properties. We are exploring the use of other agent-based methods to model self-organization and self-assembly of molecules, cells and other entities. We will present an overview of emergence in chemistry and drug discovery, and summarize some of our research into modelling important emergent properties in complex biological systems.

Biographical Notes : PhD from Monash University . Fellowships to Kyoto and Oxford

Universities. Senior Principal Research Scientist, CSIRO Molecular Science in Clayton, Adjunct Professor at Monash University, member of CSS Executive. Research interests include molecular design of bioactive agents, chemical and biological complex systems,

agent-based modelling. Current projects involve design of novel veterinary drugs for Schering Plough, design of novel antimicrobial drugs for BetaBiotics Ltd, transfer of Bayesian neural net technology to BioRAD Corp, design of focused chemical libraries using genetic algorithms, and design of novel crop protection agents for Du Pont. New projects involve design of artificial enzymes, and modelling of stem cell differentiation using ABM. Published ~120 papers, reports and book chapters and 4 patents.

Abstract : The revolution in linguistics ushered in by the publication of Noam Chomsky's "Syntactic Structures" in 1957 heralded a new era where the innateness hypothesis reigned supreme: Namely, a still as yet uncharted "language organ" within the brain enabled human beings to develop and converse in a plethora of dialects ordered according to set patterns. How did syntactic communication arise? The process of biological evolution according to theory is slow with the effects being cumulative over time. How did language, and the environment it spawns in culture, come in to existence so rapidly? This talk will briefly survey the work of scholars, such as Martin Nowak and Terrence Deacon among others, who are engaged in the notion that language is essentially an emergent phenomenon whose reason for being is more in tune with the precepts of complexity theory than with conventional biology. In addition, speculation on the emergence of culture via research dealing with so-called "small world" phenomena and related areas will be discussed.

Biographical Notes : John Lenarcic is a Physicist and Applied Mathematician by training, an Information Technology Academic by fortunate accident and an Armchair Philosopher by conscious choice. He currently ruminates at length on IT matters as a Lecturer in the School of Business Information Technology at RMIT University in Melbourne , Australia . Lenarcic's research interests include social informatics with a focus on linguistic factors in knowledge management.

A self-confessed polymath * or "jack-of-all-trades-master-of-some" as he would say * Lenarcic is also undertaking independent research into cross-cultural colour cognition in association with the National School of Design at Swinburne University of Technology. His work in this area is inherently interdisciplinary in nature, involving the Biology of Colour Vision, Linguistics, Philosophy, Anthropology, Psychology and Computer Science. It is anticipated that the outcomes of this project will be of practical relevance to the design of commercial websites that span global communities.

In his famous aphorism "It from Bit", physicist John Archibald Wheeler conjectured that physical entities arise from underlying information content. In a similar vein, if there were an all-encompassing research question driving the academic career of John Lenarcic it would most likely be "What is information?"