Download or read book Computational Evolution of Neural and Morphological Development written by Yaochu Jin and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a basic yet unified overview of theory and methodologies for evolutionary developmental systems. Based on the author's extensive research into the synergies between various approaches to artificial intelligence including evolutionary computation, artificial neural networks, and systems biology, it also examines the inherent links between biological intelligence and artificial intelligence. The book begins with an introduction to computational algorithms used to understand and simulate biological evolution and development, including evolutionary algorithms, gene regulatory network models, multi-cellular models for neural and morphological development, and computational models of neural plasticity. Chap. 2 discusses important properties of biological gene regulatory systems, including network motifs, network connectivity, robustness and evolvability. Going a step further, Chap. 3 presents methods for synthesizing regulatory motifs from scratch and creating more complex regulatory dynamics by combining basic regulatory motifs using evolutionary algorithms. Multi-cellular growth models, which can be used to simulate either neural or morphological development, are presented in Chapters 4 and 5. Chap. 6 examines the synergies and coupling between neural and morphological evolution and development. In turn, Chap. 7 provides preliminary yet promising examples of how evolutionary developmental systems can help in self-organized pattern generation, referred to as morphogenetic self-organization, highlighting the great potentials of evolutionary developmental systems. Finally, Chap. 8 rounds out the book, stressing the importance and promise of the evolutionary developmental approach to artificial intelligence. Featuring a wealth of diagrams, graphs and charts to aid in comprehension, this book offers a valuable asset for graduate students, researchers and practitioners who are interested in pursuing a different approach to artificial intelligence.

Download or read book Computational Evolution of Neural and Morphological Development written by Yaochu Jin and published by Springer Nature. This book was released on 2023-07-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a basic yet unified overview of theory and methodologies for evolutionary developmental systems. Based on the author’s extensive research into the synergies between various approaches to artificial intelligence including evolutionary computation, artificial neural networks, and systems biology, it also examines the inherent links between biological intelligence and artificial intelligence. The book begins with an introduction to computational algorithms used to understand and simulate biological evolution and development, including evolutionary algorithms, gene regulatory network models, multi-cellular models for neural and morphological development, and computational models of neural plasticity. Chap. 2 discusses important properties of biological gene regulatory systems, including network motifs, network connectivity, robustness and evolvability. Going a step further, Chap. 3 presents methods for synthesizing regulatory motifs from scratch and creating more complex regulatory dynamics by combining basic regulatory motifs using evolutionary algorithms. Multi-cellular growth models, which can be used to simulate either neural or morphological development, are presented in Chapters 4 and 5. Chap. 6 examines the synergies and coupling between neural and morphological evolution and development. In turn, Chap. 7 provides preliminary yet promising examples of how evolutionary developmental systems can help in self-organized pattern generation, referred to as morphogenetic self-organization, highlighting the great potentials of evolutionary developmental systems. Finally, Chap. 8 rounds out the book, stressing the importance and promise of the evolutionary developmental approach to artificial intelligence. Featuring a wealth of diagrams, graphs and charts to aid in comprehension, this book offers a valuable asset for graduate students, researchers and practitioners who are interested in pursuing a different approach to artificial intelligence.

Download or read book Advances in Neuro Information Processing written by Mario Köppen and published by Springer Science & Business Media. This book was released on 2009-07-10 with total page 1273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.

Download or read book From Ecology to Brain Development Bridging Separate Evolutionary Paradigms written by Francisco Aboitiz and published by Frontiers Media SA. This book was released on 2018-09-14 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nervous system is the product of biological evolution and is shaped by the interplay between extrinsic factors determining the ecology of animals, and by intrinsic processes that dictate the developmental rules that give rise to adult functional structures. This special topic is oriented to develop an integrative view from behavior and ecology to neurodevelopmental processes. We address questions such as how do sensory systems evolve according to ecological conditions? How do neural networks organize to generate adaptive behavior? How does cognition and brain connectivity evolve? What are the developmental mechanisms that give rise to functional adaptation? Accordingly, the book is divided in three sections, (i) Evolution of sensorimotor systems; (ii) Cognitive computations and neural circuits, and (iii) Development and brain evolution. We hope that this initiative will support an interdisciplinary program that addresses the nervous system as a unified organ, subject to both functional and developmental constraints, where the final outcome results of a compromise between different parameters rather than being the result of several single variables acting independently of each other.

Download or read book On Growth Form and Computers written by Sanjeev Kumar and published by Elsevier. This book was released on 2003-10-03 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conceived for both computer scientists and biologists alike, this collection of 22 essays highlights the important new role that computers play in developmental biology research. Essays show how through computer modeling, researchers gain further insight into developmental processes. Featured essays also cover their use in designing computer algorithms to tackle computer science problems in areas like neural network design, robot control, evolvable hardware, and more. Peter Bentley, noted for his prolific research on evolutionary computation, and Sanjeev Kumar head up a respected team to guide readers through these very complex and fascinating disciplines. * Covers both developmental biology and computational development -- the only book of its kind! * Provides introductory material and more detailed information on BOTH disciplines * Includes contribututions from Richard Dawkins, Lewis Wolpert, Ian Stewart, and many other experts

Download or read book Developmental Robotics written by Angelo Cangelosi and published by MIT Press. This book was released on 2015-01-09 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of an interdisciplinary approach to robotics that takes direct inspiration from the developmental and learning phenomena observed in children's cognitive development. Developmental robotics is a collaborative and interdisciplinary approach to robotics that is directly inspired by the developmental principles and mechanisms observed in children's cognitive development. It builds on the idea that the robot, using a set of intrinsic developmental principles regulating the real-time interaction of its body, brain, and environment, can autonomously acquire an increasingly complex set of sensorimotor and mental capabilities. This volume, drawing on insights from psychology, computer science, linguistics, neuroscience, and robotics, offers the first comprehensive overview of a rapidly growing field. After providing some essential background information on robotics and developmental psychology, the book looks in detail at how developmental robotics models and experiments have attempted to realize a range of behavioral and cognitive capabilities. The examples in these chapters were chosen because of their direct correspondence with specific issues in child psychology research; each chapter begins with a concise and accessible overview of relevant empirical and theoretical findings in developmental psychology. The chapters cover intrinsic motivation and curiosity; motor development, examining both manipulation and locomotion; perceptual development, including face recognition and perception of space; social learning, emphasizing such phenomena as joint attention and cooperation; language, from phonetic babbling to syntactic processing; and abstract knowledge, including models of number learning and reasoning strategies. Boxed text offers technical and methodological details for both psychology and robotics experiments.

Download or read book Bio Inspired Self Organizing Robotic Systems written by Yan Meng and published by Springer Science & Business Media. This book was released on 2011-05-08 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments. Compared with classical control methods for robotic systems, the major advantages of bio-inspired self-organizing robotic systems include robustness, self-repair and self-healing in the presence of system failures and/or malfunctions, high adaptability to environmental changes, and autonomous self-organization and self-reconfiguration without a centralized control. “Bio-inspired Self-organizing Robotic Systems” provides a valuable reference for scientists, practitioners and research students working on developing control algorithms for self-organizing engineered collective systems, such as swarm robotic systems, self-reconfigurable modular robots, smart material based robotic devices, unmanned aerial vehicles, and satellite constellations.

Download or read book Evolution of Nervous Systems written by Georg F. Striedter and published by Academic Press. This book was released on 2016-11-23 with total page 2064 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolution of Nervous Systems, Second Edition, Four Volume Set is a unique, major reference which offers the gold standard for those interested both in evolution and nervous systems. All biology only makes sense when seen in the light of evolution, and this is especially true for the nervous system. All animals have nervous systems that mediate their behaviors, many of them species specific, yet these nervous systems all evolved from the simple nervous system of a common ancestor. To understand these nervous systems, we need to know how they vary and how this variation emerged in evolution. In the first edition of this important reference work, over 100 distinguished neuroscientists assembled the current state-of-the-art knowledge on how nervous systems have evolved throughout the animal kingdom. This second edition remains rich in detail and broad in scope, outlining the changes in brain and nervous system organization that occurred from the first invertebrates and vertebrates, to present day fishes, reptiles, birds, mammals, and especially primates, including humans. The book also includes wholly new content, fully updating the chapters in the previous edition and offering brand new content on current developments in the field. Each of the volumes has been carefully restructured to offer expanded coverage of non-mammalian taxa, mammals, primates, and the human nervous system. The basic principles of brain evolution are discussed, as are mechanisms of change. The reader can select from chapters on highly specific topics or those that provide an overview of current thinking and approaches, making this an indispensable work for students and researchers alike. Presents a broad range of topics, ranging from genetic control of development in invertebrates, to human cognition, offering a one-stop resource for the evolution of nervous systems throughout the animal kingdom Incorporates the expertise of over 100 outstanding investigators who provide their conclusions in the context of the latest experimental results Presents areas of disagreement and consensus views that provide a holistic view of the subjects under discussion

Download or read book Applications of Evolutionary Computation written by Stephen Smith and published by Springer Nature. This book was released on with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Neuroanatomy The Methods written by Moo K Chung and published by World Scientific. This book was released on 2012-09-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational neuroanatomy is an emerging field that utilizes various non-invasive brain imaging modalities, such as MRI and DTI, in quantifying the spatiotemporal dynamics of the human brain structures in both normal and clinical populations. This discipline emerged about twenty years ago and has made substantial progress in the past decade. The main goals of this book are to provide an overview of various mathematical, statistical and computational methodologies used in the field to a wide range of researchers and students, and to address important yet technically challenging topics in further detail.

Download or read book Brain Evolution by Design written by Shuichi Shigeno and published by Springer. This book was released on 2017-02-07 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a new, detailed examination that explains how elegant brains have been shaped in evolution. It consists of 19 chapters written by academic professionals in neuroscience, opening with the origin of single-celled creatures and then introducing primordial types in invertebrates with the great abundance of the brains of vertebrates. Important topics are provided in a timely manner, because novel techniques emerged rapidly—as seen, for examples, in the next-generation sequencers and omics approaches. With the explosion of big data, neural-related genes and molecules is now on the radar. In fact, Europe’s big science and technology projects, a €1 billion plan called the Human Brain Project and the Blue Brain Project to understand mammalian brain networks, have been launched in recent years. Furthermore, with the rise of recently advanced artificial intelligence, there is great enthusiasm for understanding the evolution of neural networks. The views from brain evolution in nature provide an essential opportunity to generate ideas for novel neuron- and brain-inspired computation. The ambition behind this book is that it will stimulate young scientists who seek a deeper understanding in order to find the basic principles shaping brains that provided higher cognitive functions in the course of evolution.

Download or read book Advances in Artificial Life written by György Kampis and published by Springer Science & Business Media. This book was released on 2011-05-21 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 5777 and LNAI 5778 constitutes the thoroughly refereed post-conference proceedings of the 10th European Conference, ECAl 2009, held in Budapest, Hungary, in September 2009. The 141 revised full papers presented were carefully reviewed and selected from161 submissions. The papers are organized in topical sections on evolutionary developmental biology and hardware, evolutionary robotics, protocells and prebiotic chemistry, systems biology, artificial chemistry and neuroscience, group selection, ecosystems and evolution, algorithms and evolutionary computation, philosophy and arts, optimization, action, and agent connectivity, and swarm intelligence.

Download or read book Neural Darwinism written by Gerald M. Edelman and published by . This book was released on 1987-12-06 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the nation's leading neuroscientists presents a radically new view of the function of the brain and the nervous system. Its central idea is that the nervous system in each individual operates as a selective system resembling natural selection in evolution, but operating by different mechanisms. This far-ranging theory of brain functions is bound to stimulate renewed discussion of such philosophical issues as the mind-body problem, the origins of knowledge and the perceptual bases of language. Notes and Index.

Download or read book From Neuron to Cognition via Computational Neuroscience written by Michael A. Arbib and published by MIT Press. This book was released on 2016-11-11 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition. This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior. The chapters—all by leaders in the field, and carefully integrated by the editors—cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language—the core of human cognition. The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter). Contributors Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

Download or read book Illustrating Evolutionary Computation with Mathematica written by Christian Jacob and published by Elsevier. This book was released on 2001-02-23 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential capacity of intelligence is the ability to learn. An artificially intelligent system that could learn would not have to be programmed for every eventuality; it could adapt to its changing environment and conditions just as biological systems do. Illustrating Evolutionary Computation with Mathematica introduces evolutionary computation to the technically savvy reader who wishes to explore this fascinating and increasingly important field. Unique among books on evolutionary computation, the book also explores the application of evolution to developmental processes in nature, such as the growth processes in cells and plants. If you are a newcomer to the evolutionary computation field, an engineer, a programmer, or even a biologist wanting to learn how to model the evolution and coevolution of plants, this book will provide you with a visually rich and engaging account of this complex subject. * Introduces the major mechanisms of biological evolution. * Demonstrates many fascinating aspects of evolution in nature with simple, yet illustrative examples. * Explains each of the major branches of evolutionary computation: genetic algorithms, genetic programming, evolutionary programming, and evolution strategies. * Demonstrates the programming of computers by evolutionary principles using Evolvica, a genetic programming system designed by the author. * Shows in detail how to evolve developmental programs modeled by cellular automata and Lindenmayer systems. * Provides Mathematica notebooks on the Web that include all the programs in the book and supporting animations, movies, and graphics.

Download or read book Applications of Evolutionary Computation written by Paul Kaufmann and published by Springer. This book was released on 2019-04-10 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoMUSART. The 44 revised full papers presented were carefully reviewed and selected from 66 submissions. They were organized in topical sections named: Engineering and Real World Applications; Games; General; Image and Signal Processing; Life Sciences; Networks and Distributed Systems; Neuroevolution and Data Analytics; Numerical Optimization: Theory, Benchmarks, and Applications; Robotics.

Download or read book Recent Advances in Simulated Evolution and Learning written by K. C. Tan and published by World Scientific. This book was released on 2004 with total page 836 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inspired by the Darwinian framework of evolution through natural selection and adaptation, the field of evolutionary computation has been growing very rapidly, and is today involved in many diverse application areas. This book covers the latest advances in the theories, algorithms, and applications of simulated evolution and learning techniques. It provides insights into different evolutionary computation techniques and their applications in domains such as scheduling, control and power, robotics, signal processing, and bioinformatics. The book will be of significant value to all postgraduates, research scientists and practitioners dealing with evolutionary computation or complex real-world problems. This book has been selected for coverage in: . OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences. Sample Chapter(s). Chapter 1: Co-Evolutionary Learning in Strategic Environments (231 KB). Contents: Evolutionary Theory: Using Evolution to Learn User Preferences (S Ujjin & P J Bentley); Evolutionary Learning Strategies for Artificial Life Characters (M L Netto et al.); The Influence of Stochastic Quality Functions on Evolutionary Search (B Sendhoff et al.); A Real-Coded Cellular Genetic Algorithm Inspired by PredatorOCoPrey Interactions (X Li & S Sutherland); Automatic Modularization with Speciated Neural Network Ensemble (V R Khare & X Yao); Evolutionary Applications: Image Classification using Particle Swarm Optimization (M G Omran et al.); Evolution of Fuzzy Rule Based Controllers for Dynamic Environments (J Riley & V Ciesielski); A Genetic Algorithm for Joint Optimization of Spare Capacity and Delay in Self-Healing Network (S Kwong & H W Chong); Joint Attention in the Mimetic Context OCo What is a OC Mimetic SameOCO? (T Shiose et al.); Time Series Forecast with Elman Neural Networks and Genetic Algorithms (L X Xu et al.); and other articles. Readership: Upper level undergraduates, graduate students, academics, researchers and industrialists in artificial intelligence, evolutionary computation, fuzzy logic and neural networks."