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Evolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo Evo-Eco and Evolutionary Transitions

机译:进化联系主义:Evo-DevoEvo-Eco和进化转变中生物组织进化背后的算法原理

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摘要

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.
机译:自然选择的进化所依赖的变异,选择和继承的机制,在进化过程中并不固定。当前的进化生物学越来越关注于理解发展组织的进化如何改变表型变异的分布,生态关系的进化如何改变选择性环境,生殖关系的进化如何改变进化单位的遗传力。进化的主要转变尤其涉及发展,生态和生殖组织的根本变化,这些变化在更高的生物组织水平上实例化变异,选择和遗传。但是,当前的进化理论不能很好地描述这些组织如何随着进化的时间而变化,尤其是在组织的连续尺度上如何导致适应性复合体(关键问题是进化是自我参照的,即进化的产物改变了参数进化过程)。在这里,我们首先从强调共同的基本主题的角度重新解释这些领域中的中心开放性问题。然后,我们将从正在发展的工作体中得出的结论进行综合,该工作体正在通过转换公认的理论和认知学习模型的结果来构建针对这些问题的新理论方法。具体来说,记忆和学习的连接主义模型表明,简单的增量机制如何调整各个简单组件之间的关系,才能使组织表现出复杂的系统级行为并提高系统的自适应能力。我们使用“进化联系主义”一词来认识到,通过功能上等效的过程,作用于进化实体内部和之间的关系的自然选择会导致组织在进化系统中产生复杂的系统级行为,并改变自然选择的适应能力随着时间的推移。我们回顾了支持学习和进化领域之间功能对等的证据,并讨论了在解决我们对发展,生态和生殖组织尤其是主要进化过渡的理解时解决概念问题的潜力。

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