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I publish in leading journals including Evolution, Trends in Ecology and Evolution, Genetics, PLoS Computational Biology, Complexity, IEEE Transactions on Evolutionary Computation,  Philosophy and Biology, Biology Direct, Robotics and Autonomous Systems, Artificial Life, Journal of Theoretical Biology, Biosystems and Evolutionary Computation.
I am author of "Compositional evolution: the impact of sex, symbiosis and modularity on the gradualist framework of evolution" in the Vienna Series in Theoretical Biology, with MIT Press.

Full list of references on Google Scholar.

A selection of papers is presented below...

Unification of Evolution and Learning

Evolution by Natural Selection is supposed to be dumb (short-sighted) - and systems that learn are considered smart (able to take account of future consequences). But when selection acts on the relationships between things rather than the things themselves it is more intelligent than previously realised. Evolution (in this context) can be formally unified with associative learning mechanisms familiar in connectionist models of cognition and learning (i.e. neural networks).
Main works include:

How can evolution learn? (pdf)

The Evolution of Phenotypic Correlations and 'Developmental Memory' (pdf)

How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation (pdf)

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

How to fit in: The learning principles of cell differentiation

How adaptive plasticity evolves when selected against

Resolving the paradox of evolvability with learning theory: How evolution learns to improve evolvability on rugged fitness landscapes (pdf)


Evolution and Individuality

How do multiple short-sighted, self-interested entities become ‘part of something bigger than themselves’, acting together at a new level of individuality, even when this opposes the immediate individual needs of those parts? The evolutionary transitions in individuality, such as the transition from unicellular life to multicellular organisms, are poorly understood. Several topics of the 'extended evolutionary synthesis', often treated merely as 'add-ons' to the standard model, are actually vital to creating and sustaining Darwinian individuality. 

The Collective Intelligence of Development and Evolution

► Design for an Individual: Connectionist Approaches to the Evolutionary Transitions in Individuality

Are Developmental Plasticity, Niche Construction, and Extended Inheritance Necessary for Evolution by Natural Selection? The Role of Active Phenotypes in the Minimal Criteria for Darwinian Individuality

The concurrent evolution of cooperation and the population structures that support it 

Social niche construction and evolutionary transitions in individuality

Can selfish symbioses effect higher-level selection?

extended evolutionary synthesis

Adaptive Networks and their self-organisation

Evolution by natural selection is a theory that describes things and how they change in frequency. In contrast, "evolutionary connectionsim" is a theory of the relationships between things and how their organisation changes. See Liology and Complex Systems (care of Jeremy Lent). My research has studied how the organisation of networks is changed by the behaviour of the components on the network, and reflexively, the behaviour of the components on the network is changed by the organisation of the network (a.k.a. adaptive networks). This applies to systems that are not evolutionary units (do not exhibit heritable variation in reproductive success) including ecosystems and societies...

Modular interdependency in complex dynamical systems

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

Optimization in “self‐modeling” complex adaptive systems

Global adaptation in networks of selfish components: Emergent associative memory at the system scale (pdf)

What can ecosystems learn? Expanding evolutionary ecology with learning theory

“If You Can't Be With the One You Love, Love the One You're With”: How Individual Habituation of Agent Interactions Improves Global Utility

Transformations in the scale of behavior and the global optimization of constraints in adaptive networks

The Web as an Adaptive Network: Coevolution of Web Behavior and Web Structure

transformation of an energy function
ecological hysteresis
Publications: Publications
Evolution and learning
Evolution and Individuality
Adaptive networks
Evolution and optimisation
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