On crossing fitness valleys with the Baldwin Effect

Escaping local optima and crossing fitness valleys to reach higher-fitness regions of a fitness landscape is a ubiquitous concept in much writing on evolutionary difficulty. The Baldwin effect, an interaction between non-heritable lifetime plasticity (e.g. learning) and evolution, has been shown to be able to guide evolutionary change and ‘smooth out’ abrupt fitness changes in fitness landscapes –thus enabling genetic evolution that would otherwise not occur. However, prior work has not provided a detailed study or analysis on the saddle-crossing ability of the Baldwin effect in a simple multi-peaked landscape. Here we provide analytic and simulation studies to investigate the effectiveness and limitations of the Baldwin effect in enabling genotypic evolution to cross fitness valleys. We also discuss how canalisation, an aspect of many prior models of the Baldwin effect, is unnecessary for the Baldwin effect and a hindrance to its valley-crossing ability

How epigenetic evolution can guide genetic evolution (abstract)

The expression level of a gene in future generations can be modified both by genetic mutations and by the attachment of methyl groups to the DNA. Since the DNA methylation pattern along a genome is inherited, methylation patterns constitute a significant epigenetic inheritance mechanism that is subject to evolution by natural selection. The variation rate of methylation patterns is generally higher than that of DNA which suggests that evolution of methylation patterns might be more rapid than that of genetic evolution. But, common consequences of methylation, such as reduced expression of methylated genes, could also be produced by genetic changes and these would have higher heritability. The question we address in this work is how the evolution of epigenetic methylation-dependent phenotypes might interact with the evolution of genetic DNA-determined phenotypes. There is no biological mechanism known to directly transfer methyl groups into equivalent DNA changes. However, in principle an indirect mechanism could cause evolved methylation patterns to enable the subsequent evolution of equivalent genetic patterns in a manner analogous to the Baldwin effect (Baldwin, Am. Nat., 30:441-451, 1896; Jablonka et al, TREE, 13:206-210, 1998). The Baldwin effect describes how non-heritable acquired characteristics can influence the evolution of equivalent genetic characteristics without any direct Lamarckian inheritance of acquired characters. This occurs because the ability to acquire or learn a new behaviour changes the selective pressures acting on genetic changes. Specifically, genetic changes that support this behaviour, e.g. by reducing learning time by making a small part of the behaviour genetically innate, may be selected for when the learning mechanism is present even though these same genetic changes may not be selected for when the learning mechanism is absent. Over generations, the modified selection pressures so produced can cause genetic assimilation of a phenotype that was previously acquired, even to the extent of making the acquisition mechanism subsequently redundant. Thus a learned behaviour can guide the evolution of an equivalent innate behaviour (Hinton & Nowlan, Complex Systems, 1: 495-502, 1987). In the Baldwin effect a rapid mechanism of lifetime adaptation guides the relatively slow genetic evolution of the same behaviour. By analogy, Jablonka et al have suggested that “genetic adaptations may be guided by heritable induced or learnt phenotypic adaptations”. Here we hypothesise that “inherited epigenetic variations may be able to ‘hold’ an adapted state for long enough to allow similar genetic variations to catch up”, as they put it, even if the epigenetic variations are not induced or learnt but simply evolved by natural selection on methylation patterns. We assume that an individual may only express one phenotype in its lifetime, but that a given genome will persist relatively unchanged on a timescale that allows its methylome to adapt by natural selection. Thus, in contrast to the Baldwin effect, in this case two mechanisms of evolution by natural selection are coupled — one acting at a different variation rate from the other. We present a simple model to illustrate how a rapidly evolving methylome can guide a slowly evolving but highly-heritable genome. This is used to show that methylome evolution can enable genetic evolution to cross fitness valleys that would otherwise require multiple genetic changes that were each selected against. This finding suggests that the relatively rapid evolution of methylation patterns can produce novel phenotypes that are subsequently genetically assimilated in DNA evolution without direct transfer or appeal to induced phenotypes. This can enable the genetic evolution of new phenotypes that would not be found by genetic evolution alone, even if methylation is not significant in the ultimate phenotype

Is Participation in Community Media an Agent of Change?

In accounts of community media, participation is often described as a social process that is linked with social change. By encouraging participation, it is often argued, it should be possible to achieve socially progressive aims, such as civic democracy, social sustainability and the equitable redress of power imbalances. However, different conceptual frameworks of participation relate in different ways to the variable circumstances, practices and outcomes that are encompassed in community media. These differences are difficult to reconcile, as they relate to a wide range of dispositions and social phenomenon, which are themselves variable and indeterminate. The significance of participation as a conceptual tool, then, which is useful in the study of community media, must therefore be tested and re-examined in situ, and as it is related to the social practices that are observable. Using Herbert Blumer’s concept of neutral social processes, this paper draws on empirical evidence that was gathered from an extended period of ethnographically informed participation in Leicester’s community media networks. This study was undertaken as part of a doctoral thesis at the Centre for Commuting and Social Responsibility, De Montfort University, which sought to account for community media practices that were negotiated by agents acting in creative networks and situations. The conceptual underpinning of this study is an adaptation of Herbert Blumer’s assertion that social processes are neutral, and thereby necessitate a revaluation of our understanding of the frameworks of expectation that are associated with participative practices (Baugh, 1990; Blumer, 1990; Lauer & Handel, 1983)

Optimisation in ‘Self-modelling’ Complex Adaptive Systems

When a dynamical system with multiple point attractors is released from an arbitrary initial condition it will relax into a configuration that locally resolves the constraints or opposing forces between interdependent state variables. However, when there are many conflicting interdependencies between variables, finding a configuration that globally optimises these constraints by this method is unlikely, or may take many attempts. Here we show that a simple distributed mechanism can incrementally alter a dynamical system such that it finds lower energy configurations, more reliably and more quickly. Specifically, when Hebbian learning is applied to the connections of a simple dynamical system undergoing repeated relaxation, the system will develop an associative memory that amplifies a subset of its own attractor states. This modifies the dynamics of the system such that its ability to find configurations that minimise total system energy, and globally resolve conflicts between interdependent variables, is enhanced. Moreover, we show that the system is not merely ‘recalling’ low energy states that have been previously visited but ‘predicting’ their location by generalising over local attractor states that have already been visited. This ‘self-modelling’ framework, i.e. a system that augments its behaviour with an associative memory of its own attractors, helps us better-understand the conditions under which a simple locally-mediated mechanism of self-organisation can promote significantly enhanced global resolution of conflicts between the components of a complex adaptive system. We illustrate this process in random and modular network constraint problems equivalent to graph colouring and distributed task allocation problems

UK energy strategies under uncertainty: synthesis report

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Associative memory in gene regulation networks

The pattern of gene expression in the phenotype of an organism is determined in part by the dynamical attractors of the organism’s gene regulation network. Changes to the connections in this network over evolutionary time alter the adult gene expression pattern and hence the fitness of the organism. However, the evolution of structure in gene expression networks (potentially reflecting past selective environments) and its affordances and limitations with respect to enhancing evolvability is poorly understood in general. In this paper we model the evolution of a gene regulation network in a controlled scenario. We show that selected changes to connections in the regulation network make the currently selected gene expression pattern more robust to environmental variation. Moreover, such changes to connections are necessarily ‘Hebbian’ – ‘genes that fire together wire together’ – i.e. genes whose expression is selected for in the same selective environments become co-regulated. Accordingly, in a manner formally equivalent to well-understood learning behaviour in artificial neural networks, a gene expression network will therefore develop a generalised associative memory of past selected phenotypes. This theoretical framework helps us to better understand the relationship between homeostasis and evolvability (i.e. selection to reduce variability facilitates structured variability), and shows that, in principle, a gene regulation network has the potential to develop ‘recall’ capabilities normally reserved for cognitive systems

Transformations in the Scale of Behaviour and the Global Optimisation of Constraints in Adaptive Networks

The natural energy minimisation behaviour of a dynamical system can be interpreted as a simple optimisation process, finding a locally optimal resolution of problem constraints. In human problem solving, high-dimensional problems are often made much easier by inferring a low-dimensional model of the system in which search is more effective. But this is an approach that seems to require top-down domain knowledge; not one amenable to the spontaneous energy minimisation behaviour of a natural dynamical system. However, in this paper we investigate the ability of distributed dynamical systems to improve their constraint resolution ability over time by self-organisation. We use a ‘self-modelling’ Hopfield network with a novel type of associative connection to illustrate how slowly changing relationships between system components can result in a transformation into a new system which is a low-dimensional caricature of the original system. The energy minimisation behaviour of this new system is significantly more effective at globally resolving the original system constraints. This model uses only very simple, and fully-distributed positive feedback mechanisms that are relevant to other ‘active linking’ and adaptive networks. We discuss how this neural network model helps us to understand transformations and emergent collective behaviour in various non-neural adaptive networks such as social, genetic and ecological networks

Investigating invariant item ordering in the Mental Health Inventory : an illustration of the use of different methods

Invariant item ordering is a property of scales whereby the items are scored in the same order across a wide range of the latent trait and across a wide range of respondents. In the package ‘mokken’ in the statistical software R, the ability to analyse Mokken scales for invariant item ordering has recently been available and techniques for inspecting visually the item response curves of item pairs, have also been included. While methods to assess invariant item ordering are available, there have been indications that items representing extremes of distress in mental well-being scales, such as suicidal ideation, may lead to claiming invariant item ordering where it does not exist. We used the Mental Health Inventory to see if invariant item ordering was indicated in any Mokken scales derived and to see if this was being influenced by extreme items. A Mokken scale was derived indicating invariant item ordering. Visual inspection of the item pairs indicated that the most difficult item (suicidal ideation) was located far from the remaining cluster of items. Removing this item lowered invariant item ordering to an unacceptable level

Ofgem RIIO-2 Consultation : Response from the UK Energy Research Centre (UKERC)

The RIIO (Revenue=Incentives+Innovation+Outputs) model, introduced in 2013, is designed to ensure that payments to companies running the gas and electricity transmission and distribution networks are fair to network users and permit the recovery of reasonable costs in developing, maintaining and operating the networks. The network licensees’ allowed revenue is linked to their performance and should therefore offer them incentives for securing investment, driving innovation and delivering the service that customers expect. However, some commentators have suggested that the licensees have been making unjustified profits. With network charges making up around a quarter of the average household energy bill, it is anticipated that the new price control framework will be tougher and provide lower expected returns for network licensees. The RIIO-2 framework consultation is welcome. Ofgem’s final view on price control allowances will be published by the end of 2020 with the new network price controls ('RIIO-2') due to be implemented in 2021. General comments In our submission we responded to the individual points raised in the call. We also note the following: We support the proposal to reduce the price control period from 8 to 5 years. The energy system is undergoing unprecedented change, not only with continued transformation of the generation background but also major changes to the way electricity is used, such as for transport and heating. However, the rate and precise locations of these changes is uncertain. A shorter price control period will provide the opportunity for incentives and cost recovery to be adapted to the changing circumstances. Maintenance of acceptable levels of reliability while facilitating the energy system transformation at least cost requires substantial innovation in technologies, business processes and commercial arrangements. The development of new innovations and associated benefits to consumers often takes years to be realised, sometimes beyond a price control period in which network company shareholders would expect a return. We therefore support the proposal to retain dedicated innovation funding but encourage greater clarity on the scope of activities that can make use of such funding and on best practice in the generation and dissemination of evidence on proposed innovations. We welcome moves to increase the accountability of the network companies and would urge Ofgem to concentrate on those measures that have a genuine and positive impact on the network companies’ activities in the context of the whole energy system. We note that this is not restricted to the business plans submitted under RIIO-2 but extends to a whole raft of codes and interactions. These include the evolving responsibilities of the Electricity System Operator (ESO), the relationships between the ESO, the transmission owners and the Distribution Network Operators, and the processes for ensuring that the full set of codes, standards and market arrangements are coherent and fit for purpose. This is a challenging task that requires constant attention to ‘the big picture’ and sufficient resources, commitment and expertise on the part of the network owners, system operators and Ofgem. In applying tighter controls that avoid excessive returns to the network licensees’ owners, the upside and downside risks should be clearly assessed and incentives for managing risk placed on those parties best placed to do so

Managing Supply Chain Networks: A Framework for Achieving Superior Performance through Leadership Capabilities Development in Supply Chain Node

Leadership capability is acknowledged as a major challenge for organizations and a pre-requisite for sustaining high levels of organizational performance and supply chain competitiveness. Recent research highlights how globalisation has led to the extension of domestic supply chains, particularly SME ones, to include both suppliers and customers globally. This paper examines the role capabilities development in managers and leaders as nexus of their supply chain networks have to play in achieving better performance through case studies. Once banished to the backburners of business management thinking, leveraging core leadership competencies is now critical to company‟s superior performance in supply chain networks