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Books on the topic 'Evolutionary development of neural network'

Author: Grafiati

Published: 28 June 2021

Last updated: 5 February 2022

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1

Lou, Padgett Mary, Lindblad Thomas, Society for Computer Simulation, and United States. National Aeronautics and Space Administration., eds. Sixth, Seventh, and Eighth Workshops on Virtual Intelligence: Academic/Industrial/NASA/Defense: Technical interchange and tutorials : International Conferences on Virtual Intelligence, Fuzzy Systems, Evolutionary Computing, and Virtual Reality 1996. Bellingham, Wash: SPIE, 1996.

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2

C, Jain L., and Johnson R. P, eds. Automatic generation of neural network architecture using evolutionary computation. Singapore: World Scientific, 1997.

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3

Jorgensen, Charles C. Development of a sensor coordinated kinematic model for neural network controller training. [Moffett Field, Calif.?]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1990.

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4

International, Symposium on Computational Intelligence and Design (1st 2008 Wuhan China). Proceedings of the 2008 International Symposium on Computational Intelligence and Design: October 17-18, 2008, Wuhan, China. Los Alamitos, Calif: IEEE Computer Society, 2008.

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5

International Symposium on Computational Intelligence and Design (2nd 2009 Changsha, China). Proceedings: 2009 International Symposium on Computational Intelligence and Design : Changsha, China, 12-14 December 2009. Los Alamitos, Calif: IEEE Computer Society, 2008.

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6

International Symposium on Computational Intelligence and Design (3rd 2010 Hangzhou, Zhejiang, China). Proceedings: 2010 International Symposium on Computational Intelligence and Design : ICSID 2010 : 29-31 October 2010, Hangzhou, Zhejiang, China. Los Alamitos, Calif: IEEE Computer Society, 2010.

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7

International Conference on Innovative Computing, Information and Control (1st 2006 Beijing, China). ICICIC 2006: First International Conference on Innovative Computing, Information and Control : 30 August-1 September, 2006, Beijing, China. Edited by Pan Jeng-Shyang, Shi Peng 1958-, Zhao Yao, and Institute of Electrical and Electronics Engineers. Los Alamitos, Calif: IEEE Computer Society, 2006.

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8

Topping, B. H. Developments in Neural Networks and Evolutionary Computing for Civil and Structural Engineering. Hyperion Books, 1995.

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9

Semi-Empirical Neural Network Modeling and Digital Twins Development. Elsevier, 2020. http://dx.doi.org/10.1016/c2017-0-02027-x.

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10

Software Development Outsourcing Decision Support Tool with Neural Network Learning. Storming Media, 2004.

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11

Marlow, Heather, ed. Evolutionary Development of Marine Larvae. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198786962.003.0002.

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Access to a growing number of marine invertebrates with genetic and genomic tools has broadened our understanding of the diversity of developmental mechanisms, informing our understanding of larval evolution by allowing the identification of shared or divergent programs for the formation of body plan patterning and organ formation. Two such genetic programs are the apical plate patterning network and the hox/parahox trunk and gut patterning network common to larval and adult forms, respectively. While mounting evidence supports an ancient origin at the base of the Bilateria for both adult and larval forms, it is clear that many distinct organs and structures have appeared independently and can be shifted between the larval and adult phase frequently. Future advances in our understanding of larval evolution are likely to emerge from exhaustive studies of marine invertebrate cell types by single-cell sequencing technologies and through the study of the genetic basis of the metamorphic transition.

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12

Silaparasetty, Vinita. Deep Learning Projects Using TensorFlow 2: Neural Network Development with Python and Keras. Apress, 2020.

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13

Computational Intelligence and Its Applications: Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques. Imperial College Press, 2012.

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14

Domhoff, G. William. The Emergence of Dreaming. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190673420.001.0001.

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This book presents a new neurocognitive theory of dreams that documents the similarities of dreaming to waking thought, demonstrates that personal psychological meaning can be found in a majority of dream reports, has a strong developmental dimension based on excellent longitudinal and cross-sectional studies carried out in sleep labs with children ages 3–15, locates the neural substrate for dreaming in the same brain network active during mind-wandering and daydreaming, and marshals the evidence that shows it is very unlikely that dreaming has any adaptive function. These claims are based on five different sets of descriptive empirical findings that were developed between the late 1950s and the first sixteen years of the twenty-first century. All of these findings were unanticipated by scientific dream researchers and then resisted to varying degrees by dream theorists for a variety of reasons. The first five chapters spell out the theory and the evidence for it without any discussion or criticism of past theories. The next two chapters present detailed criticisms of two major alternative theories. The penultimate chapter presents evidence that it is very unlikely that dreaming has any adaptive function in the evolutionary sense of the term, although humans have invented uses for dreams in religious and healing rituals. In that regard, dreaming has an emergent function in culture that was invented in the course of history due to human cognitive capacities. The final chapter presents a general agenda for future research using new methodologies to test all of the neurocognitive hypotheses.

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15

Mundy, Peter. A Neural Networks, Information-Processing Model of Joint Attention and Social-Cognitive Development. Edited by Philip David Zelazo. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199958474.013.0010.

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A neural networks approach to the development of joint attention can inform the study of the nature of human social cognition, learning, and symbolic thought process. Joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of a distributed and integrated brain network involving frontal and parietal cortical systems. In this chapter I discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. I also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human social cognition and symbolic thinking.

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16

Panayiotou, Panayiotis Andrea. Immovable property taxation and the development of an artificial neural network valuation sysytem for residential properties for tax purposes in Cyprus. 1999.

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17

Tomanek, Robert J., Adriana A. Silva Pires-Gomes, and José Maria Pérez-Pomares. The development of coronary vascularization. Edited by José Maria Pérez-Pomares, Robert G. Kelly, Maurice van den Hoff, José Luis de la Pompa, David Sedmera, Cristina Basso, and Deborah Henderson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198757269.003.0021.

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The coronary vascular system is a complex network of arteries, veins, and capillaries that supports myocardial performance, a topic previously reviewed by other authors. Disruption of coronary blood vessel form and/or function can underlie severe congenital and acquired cardiovascular conditions, from myocardial infarction to sudden death. Coronary blood vessels are an evolutionary innovation of vertebrates and form from multiple cell sources. Accordingly, the developmental complexity of coronary vessel morphogenesis is likely to reflect evolutionary constraints, as well as to explain the origins of coronary congenital anomalies (CCAs). In this chapter we summarize the current knowledge on coronary vascular development and identify the essential mechanistic cellular and molecular components of coronary morphogenesis. We will also provide plausible developmental explanations for some relevant CCAs.

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18

(Editor), Javier Segovia, Piotr S. Szczepaniak (Editor), and Marian Niedzwiedzinski (Editor), eds. E-Commerce and Intelligent Methods. Physica-Verlag Heidelberg, 2002.

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19

1963-, Segovia Javier, Szczepaniak Piotr S. 1953, and Niedzwiedzinski Marian 1947-, eds. E-commerce and intelligent methods. Heidelberg: Physica-Verlag, 2002.

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20

Raff, Lionel, Ranga Komanduri, Martin Hagan, and Satish Bukkapatnam. Neural Networks in Chemical Reaction Dynamics. Oxford University Press, 2012. http://dx.doi.org/10.1093/oso/9780199765652.001.0001.

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This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.

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21

Mittelbach, Gary G., and Brian J. McGill. Community Ecology. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198835851.001.0001.

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Community Ecology provides a broad, up-to-date coverage of ecological concepts at the community level and is suitable for advanced undergraduates, graduate students, and ecological researchers. The field of community ecology has undergone a transformation in recent years, from a discipline largely focused on processes occurring within a local area to a discipline encompassing a much richer domain of study, including the linkages between communities separated in space (metacommunity dynamics), niche and neutral theory, the interplay between ecology and evolution (eco-evolutionary dynamics), and the influence of historical and regional processes in shaping patterns of biodiversity. To fully understand these new developments, however, students continue to need a strong foundation in the study of species interactions, and how these interactions are assembled into community modules and ecological networks. Trait-based assembly rules are presented as another approach to understanding community assembly, especially for real-world communities that may contain hundreds of species. This new edition fulfils the book’s original aims, both as a much-needed up-to-date and accessible introduction to modern community ecology, and in identifying the important questions that are yet to be answered. This research-driven textbook introduces state-of-the-art community ecology to a new generation of students, adopting reasoned and balanced perspectives on as-yet-unresolved issues. Pictures and graphics throughout the text allow students to visualize advanced concepts.

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22

Unger, Herwig, and Wolfgang A. Halang, eds. Autonomous Systems 2016. VDI Verlag, 2016. http://dx.doi.org/10.51202/9783186848109.

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To meet the expectations raised by the terms Industrie 4.0, Industrial Internet and Internet of Things, real innovations are necessary, which can be brought about by information processing systems working autonomously. Owing to their growing complexity and their embedding in complex environments, their design becomes increasingly critical. Thus, the topics addressed in this book span from verification and validation of safety-related control software and suitable hardware designed for verifiability to be deployed in embedded systems over approaches to suppress electromagnetic interferences to strategies for network routing based on centrality measures and continuous re-authentication in peer-to-peer networks. Methods of neural and evolutionary computing are employed to aid diagnosing retinopathy of prematurity, to invert matrices and to solve non-deterministic polynomial-time hard problems. In natural language processing, interface problems between humans and machines are solved with g...

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23

Ahmari, Susanne E. Targeted Circuit Manipulations in the Modeling of OCD. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0034.

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Work in animal models has great potential to shed light on the neural circuit perturbations that lead to OCD-related behaviors. Circuit-specific manipulations allow testing of the causal role of the brain network abnormalities observed in clinical imaging studies, with a precision that is not possible in investigations in humans. In recent years, circuit-specific manipulations in animals using a range of technologies have confirmed that abnormalities in the cortico-striatal circuitry can produce repetitive behaviors, such as excessive grooming. This chapter summarizes these advances. Refining our understanding of the contribution of particular neural circuits to OCD-relevant behaviors can inform the development of anatomically targeted treatments, such as deep brain stimulation.

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24

Russell, James A., and Jose Miguel Fernandez Dols, eds. The Science of Facial Expression. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190613501.001.0001.

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Organized in eleven thematic sections, The Science of Facial Expression offers a broad perspective of the “geography” of the science of facial expression. It reviews the scientific history of emotion perception and the evolutionary origins and functions of facial expression. It includes an updated compilation on the great debate around Basic Emotion Theory versus Behavioral Ecology and Psychological constructionism. The developmental psychology and social psychology of facial expressions is explored in the role of facial expressions in child development, social interactions, and culture. The book also covers appraisal theory, concepts, neural and behavioral processes, and lesser-known facial behaviors such as yawing, vocal crying, and vomiting. In addition, the book reflects that research on the “expression of emotion” is moving towards a significance of context in the production and interpretation of facial expression The authors expose various fundamental questions and controversies yet to be resolved, but in doing so, open many sources of inspiration to pursue in the scientific study of facial expression.

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25

Selverston, Allen. Rhythms and oscillations. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0021.

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The study of identifiable neurons, a common feature of invertebrate nervous systems, has made it possible to construct a detailed cell-to-cell connectivity map using electrophysiological methods that can inspire the design of biomimetic systems. This chapter describes how the analysis of the neural circuitry in the lobster stomatogastric ganglion (STG) has provided some general principles underlying oscillatory and rhythmic behavior in all animals. The rhythmic and oscillatory patterns produced by the two STG central pattern generating (CPG) circuits are a result of two cooperative mechanisms, intrinsically bursting pacemaker neurons and synaptic network properties. Also covered are the major neuromodulatory and neural control mechanisms. The chapter discusses how a deep knowledge of the stomatogastric circuitry has led to the development of electronic neurons for biomimetic devices that can be used for experimental and prosthetic applications The chapter concludes with a section on new techniques that may help with unraveling oscillatory circuits in the brain.

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26

Fox, Raymond. The Use of Self. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780190616144.001.0001.

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This monograph presents recent advances in neural network (NN) approaches and applications to chemical reaction dynamics. Topics covered include: (i) the development of ab initio potential-energy surfaces (PES) for complex multichannel systems using modified novelty sampling and feedforward NNs; (ii) methods for sampling the configuration space of critical importance, such as trajectory and novelty sampling methods and gradient fitting methods; (iii) parametrization of interatomic potential functions using a genetic algorithm accelerated with a NN; (iv) parametrization of analytic interatomic potential functions using NNs; (v) self-starting methods for obtaining analytic PES from ab inito electronic structure calculations using direct dynamics; (vi) development of a novel method, namely, combined function derivative approximation (CFDA) for simultaneous fitting of a PES and its corresponding force fields using feedforward neural networks; (vii) development of generalized PES using many-body expansions, NNs, and moiety energy approximations; (viii) NN methods for data analysis, reaction probabilities, and statistical error reduction in chemical reaction dynamics; (ix) accurate prediction of higher-level electronic structure energies (e.g. MP4 or higher) for large databases using NNs, lower-level (Hartree-Fock) energies, and small subsets of the higher-energy database; and finally (x) illustrative examples of NN applications to chemical reaction dynamics of increasing complexity starting from simple near equilibrium structures (vibrational state studies) to more complex non-adiabatic reactions. The monograph is prepared by an interdisciplinary group of researchers working as a team for nearly two decades at Oklahoma State University, Stillwater, OK with expertise in gas phase reaction dynamics; neural networks; various aspects of MD and Monte Carlo (MC) simulations of nanometric cutting, tribology, and material properties at nanoscale; scaling laws from atomistic to continuum; and neural networks applications to chemical reaction dynamics. It is anticipated that this emerging field of NN in chemical reaction dynamics will play an increasingly important role in MD, MC, and quantum mechanical studies in the years to come.

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27

Butz, Martin V., and Esther F. Kutter. How the Mind Comes into Being. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.001.0001.

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For more than 2000 years Greek philosophers have thought about the puzzling introspectively assessed dichotomy between our physical bodies and our seemingly non-physical minds. How is it that we can think highly abstract thoughts, seemingly fully detached from actual, physical reality? Despite the obvious interactions between mind and body (we get tired, we are hungry, we stay up late despite being tired, etc.), until today it remains puzzling how our mind controls our body, and vice versa, how our body shapes our mind. Despite a big movement towards embodied cognitive science over the last 20 years or so, introductory books with a functional and computational perspective on how human thought and language capabilities may actually have come about – and are coming about over and over again – are missing. This book fills that gap. Starting with a historical background on traditional cognitive science and resulting fundamental challenges that have not been resolved, embodied cognitive science is introduced and its implications for how human minds have come and continue to come into being are detailed. In particular, the book shows that evolution has produced biological bodies that provide “morphologically intelligent” structures, which foster the development of suitable behavioral and cognitive capabilities. While these capabilities can be modified and optimized given positive and negative reward as feedback, to reach abstract cognitive capabilities, evolution has furthermore produced particular anticipatory control-oriented mechanisms, which cause the development of particular types of predictive encodings, modularizations, and abstractions. Coupled with an embodied motivational system, versatile, goal-directed, self-motivated behavior, learning becomes possible. These lines of thought are introduced and detailed from interdisciplinary, evolutionary, ontogenetic, reinforcement learning, and anticipatory predictive encoding perspectives in the first part of the book. A short excursus then provides an introduction to neuroscience, including general knowledge about brain anatomy, and basic neural and brain functionality, as well as the main research methodologies. With reference to this knowledge, the subsequent chapters then focus on how the human brain manages to develop abstract thought and language. Sensory systems, motor systems, and their predictive, control-oriented interactions are detailed from a functional and computational perspective. Bayesian information processing is introduced along these lines as are generative models. Moreover, it is shown how particular modularizations can develop. When control and attention come into play, these structures develop also dependent on the available motor capabilities. Vice versa, the development of more versatile motor capabilities depends on structural development. Event-oriented abstractions enable conceptualizations and behavioral compositions, paving the path towards abstract thought and language. Also evolutionary drives towards social interactions play a crucial role. Based on the developing sensorimotor- and socially-grounded structures, the human mind becomes language ready. The development of language in each human child then further facilitates the self-motivated generation of abstract, compositional, highly flexible thought about the present, past, and future, as well as about others. In conclusion, the book gives an overview over how the human mind comes into being – sketching out a developmental pathway towards the mastery of abstract and reflective thought, while detailing the critical body and neural functionalities, and computational mechanisms, which enable this development.

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28

Barwich, Ann-Sophie. Measuring the World. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198779636.003.0017.

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How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes.

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29

Zamarian, L., and Margarete Delazer. Arithmetic Learning in Adults. Edited by Roi Cohen Kadosh and Ann Dowker. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199642342.013.007.

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Neuroimaging has significantly contributed to our understanding of human learning by tracking the neural correlates underlying the acquisition of new expertise. Studies using functional magnetic resonance imaging (fMRI) suggest that the acquisition of arithmetic competence is reflected in a decrease of activation in frontal brain regions and a relative increase of activation in parietal brain regions that are important for arithmetic processing. Activation of the angular gyrus (AG) is related to fact learning, skilled retrieval, and level of automatization. fMRI investigations extend the findings of cognitive studies showing that behavioural differences between trained and untrained sets of items, between different arithmetic operations, and between different training strategies are reflected by specific activation patterns. fMRI studies also reveal inter-individual differences related to arithmetic competence, with low performing individuals showing lower AG activation when answering calculation problems. Importantly, training attenuates inter-individual differences in AG activation. Studies with calculation experts suggest that different strategies may be used to achieve extraordinary performance. While some experts recruit a more extended cerebral network compared with the average population, others use the same frontoparietal network, but more efficiently. In conclusion, brain imaging studies on arithmetic learning and expertise offer a promising view on the adaptivity of the human brain. Although evidence on functional or structural modifications following intervention in dyscalculic patients is still scarce, future studies may contribute to the development of more efficient and targeted rehabilitation programmes after brain damage or in cases of atypical numerical development.

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30

Ocampo, José Antonio. Resetting the International Monetary (Non)System. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198718116.001.0001.

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This book provides an analysis of the global monetary system and the necessary reforms that it should undergo to play an active role in the twenty-first century. As its title indicates, its basic diagnosis is that it is an ad hoc framework rather than a coherent system—a ‘non-system’—which evolved after the breakdown of the original Bretton Woods arrangement in the early 1970s. The book places a special focus on the asymmetries that emerging and developing countries face within the current system, and therefore on the development dimensions of the global monetary system and of global monetary reform. The book proposes a comprehensive yet evolutionary reform of the system that includes: (i) provision of international liquidity through a system that mixes the multi-currency arrangement with a more active use of the IMF’s Special Drawing Rights (SDRs), the only true global currency that has been created; (ii) stronger mechanisms of macroeconomic policy cooperation, including greater cooperation in exchange rate management, and freedom to manage capital flows as a complement to counter-cyclical macroeconomic policy and other instruments of financial regulation; (iii) additional automatic balance-of-payments financing facilities, and the complementary use of swap and regional arrangements; (iv) a multilateral sovereign debt workout mechanism; and (v) major reforms of the system’s governance, based on a more representative apex organization, more equitable participation of emerging and developing countries in decision-making, and a network of global, regional, inter-regional, and sub-regional organizations.

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