Engineering the Anthropocene: Scalable social networks and resilience building in human evolutionary timescales

The Anthropocene represents the emergence of human societies as a ‘great force of nature’. To understand and engage productively with this emergent global force, it is necessary to understand its origins, dynamics and structuring processes as the long-term evolutionary product of human niche construction, based on three key human characteristics: tool making, habitat construction and most importantly: social network engineering. The exceptional social capacities of behaviourally modern humans, constituting human ultrasociality, are expressed through the formation of increasingly complex and extensive social networks, enabling flexible and diverse group organisation, sociocultural niche construction, engineered adaptation and resilience building. The human drive towards optimising communication infrastructures and expanding social networks is the key human adaptation underpinning the emergence of the Anthropocene. Understanding the deep roots of human ultrasocial behaviour is essential to guiding contemporary societies towards more sustainable human–environment interactions in the Anthropocene present and future. We propose that socially networked engineered solutions will continue to be the prime driver of human resilience and adaptive capacity in the face of global environmental risks and societal challenges such as climate change, sea-level rise, localised extreme weather events and ecosystem degradation

Understanding evolutionary processes during past Quaternary climatic cycles: Can it be applied to the future?

Climate change affected ecological community make-up during the Quaternary which was probably both the cause of, and was caused by, evolutionary processes such as species evolution, adaptation and extinction of species and populations

Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

Neutral networks of genotypes: Evolution behind the curtain

Our understanding of the evolutionary process has gone a long way since the publication, 150 years ago, of "On the origin of species" by Charles R. Darwin. The XXth Century witnessed great efforts to embrace replication, mutation, and selection within the framework of a formal theory, able eventually to predict the dynamics and fate of evolving populations. However, a large body of empirical evidence collected over the last decades strongly suggests that some of the assumptions of those classical models necessitate a deep revision. The viability of organisms is not dependent on a unique and optimal genotype. The discovery of huge sets of genotypes (or neutral networks) yielding the same phenotype --in the last term the same organism--, reveals that, most likely, very different functional solutions can be found, accessed and fixed in a population through a low-cost exploration of the space of genomes. The 'evolution behind the curtain' may be the answer to some of the current puzzles that evolutionary theory faces, like the fast speciation process that is observed in the fossil record after very long stasis periods.Comment: 7 pages, 7 color figures, uses a modification of pnastwo.cls called pnastwo-modified.cls (included

Darwinism, probability and complexity : market-based organizational transformation and change explained through the theories of evolution

The study of transformation and change is one of the most important areas of social science research. This paper synthesizes and critically reviews the emerging traditions in the study of change dynamics. Three mainstream theories of evolution are introduced to explain change: the Darwinian concept of survival of the fittest, the Probability model and the Complexity approach. The literature review provides a basis for development of research questions that search for a more comprehensive understanding of organizational change. The paper concludes by arguing for the development of a complementary research tradition, which combines an evolutionary and organizational analysis of transformation and change

Evolution in Economic Geography: Institutions, Regional Adaptation and Political Economy

Economic geography has, over the last decade or so, drawn upon ideas from evolutionary economics in trying to understand processes of regional growth and change, with the concept of path dependence assuming particular prominence. Recently, some prominent researchers have sought to delimit and develop an evolutionary economic geography (EEG) as a distinct approach, aiming to create a more coherent and systematic theoretical framework for research. This paper contributes to debates on the nature and development of EEG. It has two main aims. First, we seek to restore a broader conception of social institutions and agency to EEG, informed by the recent writings of institutional economists like Geoffrey Hodgson. Second, we link evolutionary concepts to political economy approaches, arguing that the evolution of the economic landscape must be related to the broader dynamics of capital accumulation, centred upon the creation, realisation and geographical transfer of value. As such, we favour the utilisation of evolutionary and institutional concepts within a geographical political economy approach rather than the construction of a separate and theoretically ‘pure’ EEG; evolution in economic geography, not an evolutionary economic geography

Global adaptation in networks of selfish components: emergent associative memory at the system scale

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. Such global functions within a single agent or organism are not wholly surprising since the mechanisms (e.g. Hebbian learning) that create these neural organisations may be selected for this purpose, but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviours when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully-distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g. when they can influence which other agents they interact with) then, in adapting these inter-agent relationships to maximise their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviours as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalise by idealising stored patterns and/or creating new combinations of sub-patterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviours in the same sense, and by the same mechanism, as the organisational principles familiar in connectionist models of organismic learning

Evolutionary robotics and neuroscience

No description supplie