David G. Green

David G. Green
Monash University (Australia) · Faculty of Information Technology

PhD

About

228
Publications
14,286
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Introduction
David G. Green currently works at the Faculty of Information Technology, Monash University (Australia). David does research in Complex Systems, Networks, Computer and Society, Artificial Intelligence and Theory of Computation. His current projects include "Universal measurement" and "Complexity in Landscape Ecology" (2nd edition).

Publications

Publications (228)
Book
Why do things go wrong? Why, despite all the planning and care in the world, do things go from bad to worse? This book argues that it is because we are like the ants. Just as ants create an anthill without being aware of it, unintended side effects of human activity create all manner of social trends and crises. The book traces the way these trends...
Article
Full-text available
Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are t...
Article
This study explores the evolving structure of the rising field of “network of networks” (NoN). Reviewing publications dating back to 1931, we describe the evolution of major NoN research themes in different scientific disciplines and the gradual emergence of an integrated field. We analyse the co-occurrence networks of keywords used in all 7818 sci...
Preprint
Measurement theory is the cornerstone of science, but no equivalent theory underpins the huge volumes of non-numerical data now being generated. In this study, we show that replacing numbers with alternative mathematical models, such as strings and graphs, generalises traditional measurement to provide rigorous, formal systems (`observement') for r...
Chapter
Complexity is the richness and variety often seen in large systems. Species diversity is often used to represent complexity in ecosystems, but true complexity arises from the enormous number of ways to order combinations of objects. To manage the natural world successfully, we need to understand ecological complexity.
Chapter
Complexity often arises in the way things are distributed in a landscape. Sampling is subject to scale and can display properties of fractals. Cellular automata, which represent a landscape as a grid of sites, are often used to model processes in landscapes. These models highlight the phase change that occurs between connected and fragmented landsc...
Chapter
Simulation is an essential tool for understanding complexity in ecology. Virtual experiments, using simulation models, make it possible to cope with the large time and spatial scales of many ecological processes. This need has given rise to the field of Artificial Life, as well as growing use of virtual reality.
Chapter
Environmental changes, whether natural or human-made, trigger complex cascades of consequences. Such cascades played a role in the collapse of past civilisations. Those events provide lessons for current ecological challenges, especially global climate change and loss of biodiversity. The economic imperative for constant growth poses a major challe...
Chapter
In fragmented landscapes, species are often found in spatially separated, but interacting metapopulations. The combination of dispersal, competition and environmental variations lead to distribution patterns, especially clumps, patches, boundaries and zones. Pollen and charcoal analyses show that fires can trigger rapid changes in forest compositio...
Chapter
Networks are inherent in all complex systems. Patterns of interactions influence system behaviour. Many kinds of large scale patterns emerge from local interactions, including critical collapse. Ecosystems are really interconnected networks of many kinds, so changed conditions in one network can affect the entire ecosystem. One example of this was...
Chapter
The patterns we see in the growth of a plant or the behaviour of animals can appear very complex, but there are often simple rules that underlie what we see. Systems of rules, called L-systems can capture the organisation of branching patterns and other features of growing plants. Simple rules of behaviour can explain many features of animal behavi...
Chapter
New technologies are helping us to study and understand complexity of ecosystems in detail. Transformative technologies include more sophisticated methods for monitoring (sensors, remote sensing, drones); greater abilities to embrace broadscale phylogeography, and access to the power of e-science (big-data, simulation, visualisation). International...
Chapter
Species adaptation often involves trade-offs between selection for competing needs. Connected landscapes inhibit evolutionary divergence, but heterogeneity, gradients and fragmentation can all create conditions in which evolutionary variation increases. Disturbances create conditions for bursts of diversification by altering landscape connectivity.
Chapter
Complexity in landscapes, especially the effect of the connectivity avalanche, influences fundamental ecological processes, such as competition and invasion. Positive and negative feedback play crucial roles in food webs and determine whether complex ecosystems are stable. Structural complexity, including landscape patterns and species mix, is cruc...
Chapter
Ecosystems are dynamic and apparent stability may be an illusion of scale. Some ecosystems are subject to chronic disturbance. In dynamic systems, equilibrium is difficult to achieve and maintain. Systems often exhibit sensitivity to initial conditions and chaotic behaviour. Negative feedback promotes stability. Positive feedback is destabilizing,...
Book
This book examines key concepts and analytical approaches in complexity theory as it applies to landscape ecology, including complex networks, connectivity, criticality, feedback, and self-organisation. It then reviews the ways that these ideas have led to new insights into the nature of ecosystems and the role of processes in landscapes. The updat...
Chapter
Interactions within groups of people lead to many forms of aberrant social psychology. One is pluralistic ignorance (PI), in which the majority of people in a group express opinions that differ from their real beliefs. PI occurs for various reasons: one is the drive to belong to a group. To understand how PI emerges, this study presents an agent-ba...
Article
For artificial agents trading off exploration (food seeking) versus (short-term) exploitation (or consumption), our experiments suggest that uncertainty (interpreted information, theoretically) magnifies food seeking. In more uncertain environments, with food distributed uniformly randomly, exploration appears to be beneficial. In contrast, in bias...
Conference Paper
Full-text available
We propose a new model to quantitatively estimate the accuracy of artificial agents over cognitive tasks of approximable complexities. The model is derived by introducing notions from algorithmic information theory into a well-known (psychometric) measurement paradigm called Item Response Theory (IRT). A lower bound on accuracy can be guaranteed wi...
Chapter
Full-text available
Nature has inspired many algorithms for solving complex problems. Understanding how and why these natural models work leads not only to new insights about nature, but also to an understanding of deep relationships between familiar algorithms. Here, we show that network properties underlie and define a whole family of nature-inspired algorithms. In...
Research
Full-text available
In our recent work on the measurement of (collective) intelligence , we used a dynamic intelligence test to measure and compare the performances of artificial agents. In this paper we give a detailed technical description of the testing framework, its design and implementation, showing how it can be used to quantitatively evaluate general purpose,...
Conference Paper
Full-text available
The intelligence of multiagent systems is known to depend on the communication and observation abilities of its agents. However it is not clear which factor has the greater influence. By following an information-theoretical approach, this study quantifies and analyzes the impact of these two factors on the intelligence of multiagent systems. Using...
Data
Full-text available
Why do things go wrong? Why, despite all the planning and care in the world, do things go from bad to worse? This book argues that it is because we are like the ants. Just as ants create an anthill without being aware of it, unintended side effects of human activity create all manner of social trends and crises. The book traces the way these trends...
Article
h i g h l i g h t s • Introducing a new direction in mobile P2P query processing for RNN queries. • Proposing and evaluating three different search algorithms: BFA, RBA and TBA. • Substantially saving more time and energy compared with the centralised system. • TBA outperforms by filtering unnecessary peers and maintaining high accuracy rate. a b s...
Article
Group target tracking is a challenge for sensor networks. It occurs where large numbers of closely spaced targets move together in different groups. In these applications, the sensor selection scheme plays a vital role in extending network lifetime while providing high tracking accuracy. Existing schemes cause an extreme imbalance between energy us...
Chapter
May be the word “complexity” does not stand out in our daily conversations. Its meaning, however, is inherent in many of our daily discussions. When we ask how did my child understand what I just said? or how did this person commit a murder when they lived a quiet decent life? When we see sudden transitions that make people and systems behave in a...
Chapter
Optimization algorithms impose an implicit network structure on fitness landscapes. For a given algorithm A operating on a problem that has a fitness landscape F, connections between solutions are defined by the transitions allowed by A.
Chapter
Classic evolutionary algorithms (EAs) use a single population (panmixia) of individuals and apply operators on them as a whole. To prevent EAs from concentrating on a small search space area, structured EAs have been proposed to as a means for improving the search properties, which started from the parallel implementation of EAs [1–4]. This kind of...
Chapter
Networks are structures composed of sets of nodes and edges.
Chapter
In the previous chapter, we introduced that the standard population used in EAs is the panmictic one, and structured populations have been proposed to as a means for improving the search properties because several researchers have suggested that EAs populations might have structures endowed with spatial features, like many natural populations.
Chapter
Links between people form networks of connections. These social connections have always been important in society. Patterns of connections go hand in hand with the nature of peer influence involved. Families, power structures and other hierarchies lead to social networks with tree structures. Traditional social networks are constrained by time and...
Chapter
People like simple solutions to life’s challenges, and reject complex solutions. However many things in life are complex. By seeking simple solutions we overlook important connections. Interactions and relationships between people and events form networks of connections. It is the richness and variety of those connections that creates complexity. L...
Chapter
The introduction of new technologies has made enormous changes to family life. During the second half of the Twentieth century, the introduction of labour-saving devices into the family home led to huge social changes. By creating more free time, these devices set off a cascade of flow-on side effects, including increases in married women in the wo...
Chapter
The usual way of dealing with complexity is to try to reduce it by “divide-and-rule”. You carve a big problem into smaller, self-contained parts that are easier to deal with. Familiar examples range from designing houses with bedrooms and bathrooms, to dividing large organizations into sections with specialist roles. This classic approach leads to...
Chapter
The network model reveals deep similarities between social changes and many natural phenomena. The spread of ideas and epidemics, for instance, are both examples of percolation. An important process is the “connectivity avalanche” in which a network undergoes a phase transition from a fragmented set of nodes to a single connected whole. Models of c...
Chapter
Society has evolved many ways to eliminate extreme situations and to reduce their impact. Institutions such as emergency services deal with extremes. Laws and customs seek to eliminate extreme behaviour. Standardization aims to remove isolated products and practices. Media reporting distorts public perception of issues by focussing on extreme event...
Chapter
Sometimes one event leads to another, forming a chain of causation that produces unanticipated consequences. During travel, a small initial delay can grow to result in very late arrival. Government action to improve safety can lead to increasingly complex and restrictive rules and to undesirable outcomes, such as the restrictive “nanny state”. The...
Chapter
The complexity of the world around us means that unwelcome events are often sudden and unexpected. Limitations of our thinking contribute: our models of the world around us are necessarily limited in scope and detail. Also human perception is local, so we are not able to see everything that might affect us. Being unable to understand the complexity...
Chapter
Unexpected trends, events and even disasters happen all too frequently in modern society. These events range from problems facing us as individuals to national disasters. They are symptoms of the complexity of modern society. In many cases they arise as unintended side effects of every day activity. Complexity means that in any complex situation, a...
Chapter
Every new technology has social side effects. Most are unintentional. Massive social changes accompanied the Industrial Revolution. The Information Revolution is likely to set off equally wide-sweeping changes in society. Notable changes are the appearance of new media for communication, the use of “big data” in decision-making and the spread of au...
Chapter
Often, the world around us is more complex than we know. Of necessity, the models we build to explain the world simplify things by omitting many details. These omissions explain why experts are so often wrong. They also underlies serendipity, an important source of discovery in science. Because models cannot always predict the future behaviour of c...
Chapter
Advances in computing and communications have created an information explosion. Information is now an important social and commercial commodity, as exemplified by expressions such as big data and data mining. Instant communications have created a global society in which Western culture is spreading worldwide, placing minority cultures at risk. Mass...
Chapter
Human self-interest, together with side effects of new technologies will ensure that unexpected trends continue to emerge in the future. The information revolution is still underway. Many social effects of new technologies, especially in automation and robotics, are still to come. Trends in biosciences suggest that a biotechnology revolution may be...
Chapter
Many problems arise from limited thinking. Our mental models—the ways we think about the world around us—are limited by our experience. Gaps in these models mean that unexpected conditions often arise. When confronted with conditions we have never encountered before, our models fail. Accidents and other disasters may follow. A contributing factor i...
Chapter
Person-to-person interactions underlie many kinds of group behaviour, from panicking crowds, to clothing fads, to booms and busts in the share market. The growth of the Internet, for example, led to the dot-com bubble at the turn of the Millennium. Communication provides the glue that keeps social groups together. Peer pressure forces people to con...
Chapter
Events sometimes form cycles in which the outcome of one event feeds back into itself, leading to ever bigger consequences, or “positive feedback”. Examples include cycles of revenge between rival groups, growth of compound interest, and the formation of market price “bubbles”. In contrast to negative feedback, which dampens change, positive feedba...
Chapter
The world’s economy is based on the assumption of continual growth. Industries have exploited every possible means to sustain and expand markets. One effect has been to increase the levels of personal debt in many western countries. Social fragmentation and isolation help to convert traditional social support activities into service industries. Cor...
Chapter
Modern humans inherit needs and behaviours from our animal ancestors. These include the desire to belong to a group, the drive for high status within a group and the need for territory and resources. These drives are the seeds of many social problems. Fear of exclusion provides powerful motivation to conform. Leaders exploit this fear, and outside...
Chapter
In recent time, economic and population growth has been sustained by removing wilderness, by removing problems to remote areas and by technological advances such as the Green Revolution. However, unconstrained growth is now encountering the physical limits of the natural environment. People fail to respond to environmental change because the vast s...
Chapter
In a virtual landscape you can burn a forest and watch it grow back over hundreds of years, an experiment you could never do in reality. Increasingly, landscape ecology and environmental management use simulation and 3D graphics to investigate complex interactions between the environment and living things. Although some technical issues, especially...
Chapter
Many scientists have mainly focused their attention on growing networks in which a new node is added to networks with time [1]. However, as indicated by Jin et al. [2], growth models of this type are quite inappropriate as models of the growth of social networks, and one of the reasons is although new vertices are of course added to social networks...
Conference Paper
Full-text available
The increasing use of location-based services has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Group k-Nearest Neighbour (GkNN). A typical example of a GkNN query is finding one or many nearest meeting places for a group of people. Existing methods mostly rely on a centralised base sta...
Book
The aim of the book is to lay out the foundations and provide a detailed treatment of the subject. It will focus on two main elements in dual phase evolution: the relationship between dual phase evolution and other phase transition phenomena and the advantages of dual phase evolution in evolutionary computation and complex adaptive systems. The boo...
Conference Paper
Full-text available
The increasing use of mobile communications has raised many issues of decision support and resource allocation. A crucial problem is how to solve queries of Reverse Nearest Neighbor (RNN). An RNN query returns all objects that consider the query object as their nearest neighbor. Existing methods mostly rely on a centralized base station. However, m...
Conference Paper
Microblogging services, such as Twitter, generate huge volumes of data reflecting the current zeitgeist. As such they are of enormous potential value to studies ranging from data mining to social anthropology. To realize the potential, this study investigates improvements of algorithms specifically tailored for the discovery of latent socio-demogra...
Conference Paper
Social media have rapidly become one of the principal venues for personal and public communication. This makes them rich sources of information about real-world events. As a case study, we used Twitter metadata to investigate social dimensions of the 2011 London riots. The results showed that Twitter-based commentary and participation in the London...
Conference Paper
Efficient target tracking applications require active sensor nodes to track a cluster of moving targets. Clustering could lead to significant cost improvement as compared to tracking individual targets. This paper presents accurate clustering of targets for both coherent and incoherent movement patterns. We propose a novel clustering algorithm that...
Conference Paper
Complex target tracking applications require active sensor nodes to collaboratively track multiple moving targets, which can balance the trade-off between the quality of tracking and network's lifetime. In this paper, we develop a distributed sensor-selection protocol (DSSP) to activate dynamic number of sensors based on the cost metrics. Cost metr...
Article
Molecular simulation models are increasingly important tools in efforts to understand the role that water plays in biochemical processes. However, existing models of water have limited capacity to deal with the characteristics of hydrogen bond networks. This article proposes a new fluctuating network (FN) algorithm as an extension of the standard m...
Conference Paper
Wireless sensor networks are an important new technology for remote monitoring. How to organize the nodes in a network remains a core practical problem. Node clustering is the most popular technique to increase the energy efficiency of a wireless sensor network, but the number of clusters greatly influences two performance metrics - data reliabilit...
Chapter
Nature has evolved ways to solve many kinds of complex problems. Investigating these natural ‘solutions’ is a fruitful source of insights about the nature of complexity, and about ways to manage complex systems. Increasingly it is apparent that instead of trying to design complex systems it is often better to build systems that can evolve into robu...
Chapter
Modern computing is intimately bound up with complexity theory. This chapter explores this intimate relationship and its applications in complexity theory. The need to deal with complex problems has motivated many ideas and issues in computing. Conversely, computing, and computational ideas, have also played a prominent role in the development of c...
Article
Here I show that digraphs (directed graphs) are inherent both in the relationships between elements of biological systems and in transitions between different system states. Properties of digraphs therefore underlie many biological phenomena, especially criticality and phase changes. Examples include epidemics, development, vegetation change and ev...
Article
Full-text available
One of the major challenges in the field of evolutionary algorithms (EAs) is to characterise which kinds of problems are easy and which are not. Researchers have been attracted to predict the behaviour of EAs in different domains. We introduce fitness landscape networks (FLNs) that are formed using operators satisfying specific conditions and defin...
Article
Understanding complex networks in the real world is a nontrivial task. In the study of community structures we normally encounter several examples of these networks, which makes any statistical inferencing a challenging endeavor. Researchers resort to computer-generated networks that resemble networks encountered in the real world as a means to gen...
Article
Pollen diagrams from sites in southwest Nova Scotia and close to the New Brunswick – Nova Scotia border show that after retreat of the Wisconsin ice sheets, most tree taxa arrived in the extreme southwest of Nova Scotia earlier than anywhere else in the province. For most tree taxa, arrival times at sites in maritime Canada and in northeastern New...
Article
The need to understand and manage complex systems is increasing in importance, but complexity theory is still hampered by being highly fragmented in nature. This article argues that many elements for a general theory of complexity now exist and briefly reviews the main features. First, the universal nature of network model of complexity provides a...
Conference Paper
Both separated and overlapping communities are useful to analyze real networks in different situations. However, to the best of our knowledge, existing community detection methods based on Evolutionary Algorithms (EAs) can detect separate communities only. This is because it is difficult to represent overlapping communities in ways that are suitabl...
Article
The complexity of modern society leads to many unplanned social trends. Here we identify the four most common sources processes of unintended trends: brittleness of “divide and rule” strategies, failure of system models, changes in network connectivity and positive feedback. To illustrate the role these processes have played we examine three case s...
Technical Report
Full-text available
Recent studies have shown that repeated phase changes in large networks (dual phase evolution -DPE) play a role in the evolution of many kinds of systems. However, the contribution of DPE to the origin of modular adaptations remains to be demonstrated. Despite plausible arguments and suggestive evidence from natural systems, a clear proof of the ad...
Conference Paper
Background/Question/Methods We all know that ecological systems are complex, but only recently has it become clear that many features of complex systems emerge from universal properties of networks. Networks arise whenever interactions take place among a set of objects. This leads us to ask, what insights can network properties and behavior provi...
Conference Paper
Dual Phase Evolution (DPE) is a widespread natural process in which complex systems adapt and self-organise by switching alternately between two phases: a phase of global interactions and a phase of local interactions. We show that in evolving networks of agents, DPE can give rise to a wide variety of topologies. In particular, it can lead to the s...
Article
Full-text available
Spatially-explicit, individual based models are used to explore the consequences of introducing two simple genetic tradeoff mechanisms to the gradient response of monoecious diploid individuals. A simple linear gradient is used to produce a structured environment. One tradeoff relates the plasticity of an individual to its overall fitness, where in...
Conference Paper
Full-text available
In many social contexts, organisation emerges through interactions between individuals, and not by design. Often these interactions occur in two different phases: a local phase in which closely related individuals interact, and a global phase, in which individuals interact more widely within a community. We show that this Dual Phase Evolution (DPE)...
Article
Full-text available
Analytical models show that high-dimensional fitness landscapes form "holey" rather than "rugged" topographies, but the implications of this finding for biological and artificial life systems remain largely unexplored. One of the reasons for this gap can be attributed to serious difficulties in the implementation of individual-based holey fitness l...
Article
Full-text available
A key challenge in complexity theory is to understand self-organization: how order emerges out of the interactions between elements within a system. [1980] pointed out that in dissipative systems (open systems that exchange energy with their environment), order can increase. Rather then being suppressed, positive feedback allows local irregularitie...
Chapter
Modularity is ubiquitous in complex adaptive systems. Modules are clusters of components that interact with their environment as a single unit. They provide the most widespread means of coping with complexity, in both natural and artificial systems. When modules occur at several different levels, they form a hierarchy. The effects of modules and hi...
Chapter
Modularity is ubiquitous in complex adaptive systems. Modules are clusters of components that interact with their environment as a single unit. They provide the most widespread means of coping with complexity, in both natural and artificial systems. When modules occur at several different levels, they form a hierarchy. The effects of modules and hi...
Book
This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisation; hybrid learn...
Conference Paper
In this study, we describe an evolutionary mechanism – Dual Phase Evolution (DPE) – and argue that it plays a key role in the emergence of internal structure in complex adaptive systems (CAS). Our DPE theory proposes that CAS exhibit two well-defined phases – selection and variation – and that shifts from one phase to the other are triggered by ext...
Article
We provide a brief overview of the use of FLs in evolutionary biology and introduce an FL model suitable for individual-based models of species evolution. Our model combines different features of several analytic FL models used in evolutionary biology. Our new model overcomes several difficulties encountered with previous FL models, particularly ar...
Conference Paper
Social order and unity require consensus among individuals about cooperation and other issues. Boolean network models (BN) help to explain the role played by peer interactions in the emergence of consensus. BN models represent a society as a network in which individuals are the nodes (with two states, e.g. agree/disagree) and social relationships a...
Article
Biomolecular studies point increasingly to the importance of modularity in the organization of the genome. Processes such as the maintenance of metabolism are controlled by suites of genes that act as distinct, self-contained units, or modules. One effect is to promote stability of inherited characters. Despite the obvious importance of genetic mod...
Conference Paper
In classifier fusion models, classifiers outputs are combined to achieve a group decision. The most often used classifiers fusion models are majority vote, probability schemes, weighted averaging and Bayes approach to name few. We propose a model of classifiers fusion by combining the mathematical belief of classifiers. We used Dempster-Shafer theo...
Chapter
A useful way of modelling forests is to represent them as cellular automata, that is as mosaics in which each cell represents an area of the land surface. Theoretical studies using such models have revealed aspects of fire behaviour and forest dynamics that are not apparent in other models. They also mirror both traditional quadrat sampling and pix...