title: Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.
abstract: 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.
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK ; Institute for Life Sciences, University of Southampton, Southampton, UK.
authors.forename: Richard A
authors.initials: RA
authors.lastname: Watson
authors.affiliation: Biosystems & Integrative Sciences Institute (BioISI), Faculty of Sciences, University of Lisbon, Lisbon, Portugal.
authors.forename: Rob
authors.initials: R
authors.lastname: Mills
authors.affiliation: School of Engineering and Informatics, University of Sussex, Falmer, UK.
authors.forename: C L
authors.initials: CL
authors.lastname: Buckley
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Kostas
authors.initials: K
authors.lastname: Kouvaris
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Adam
authors.initials: A
authors.lastname: Jackson
authors.affiliation: University of Lausanne, Lausanne, Switzerland.
authors.forename: Simon T
authors.initials: ST
authors.lastname: Powers
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Chris
authors.initials: C
authors.lastname: Cox
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Simon
authors.initials: S
authors.lastname: Tudge
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Adam
authors.initials: A
authors.lastname: Davies
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Loizos
authors.initials: L
authors.lastname: Kounios
authors.affiliation: Agents, Interactions and Complexity, ECS, University of Southampton, Southampton, UK.
authors.forename: Daniel
authors.initials: D
authors.lastname: Power
keywords: Evolutionary developmental biology; Evolutionary ecology; Learning theory; Major transitions in evolution