Publications
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)
►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
►The concurrent evolution of cooperation and the population structures that support it
►Social niche construction and evolutionary transitions in individuality
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
►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
►The Web as an Adaptive Network: Coevolution of Web Behavior and Web Structure
Evolution and Optimisation
Evolutionary algorithms are computational optimisation methods inspired by natural selection. New ways of thinking about biological evolution inspire new computational methods.
► Deep Optimisation: Multi-scale Evolution by Inducing and Searching in Deep Representations (a,b)
► Is evolution by natural selection the algorithm of biological evolution?
► Reducing local optima in single-objective problems by multi-objectivization
► Reducing bloat and promoting diversity using multi-objective methods
► Modeling building-block interdependency
► Symbiotic combination as an alternative to sexual recombination in genetic algorithms
► A computational model of symbiotic composition in evolutionary transitions
► A building-block royal road where crossover is provably essential (pdf)
► Analysis of recombinative algorithms on a non-separable building-block problem
► A simple two-module problem to exemplify the benefit of crossover (pdf)
