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Author : Ed Hopkins
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.F/5 ( download)
Download or read book Learning and Evolution in a Heterogeneous Population written by Ed Hopkins and published by . This book was released on 1994 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4.:/5 (221 download)
Download or read book Learning and evolution in a heterogenous population written by and published by . This book was released on 1994 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Irina Kareva
Publisher : Academic Press
ISBN 13 : 0128144327
Total Pages : 354 pages
Book Rating : 4.1/5 (281 download)
Download or read book Modeling Evolution of Heterogeneous Populations written by Irina Kareva and published by Academic Press. This book was released on 2019-10-16 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling Evolution of Heterogeneous Populations: Theory and Applications describes, develops and provides applications of a method that allows incorporating population heterogeneity into systems of ordinary and discrete differential equations without significantly increasing system dimensionality. The method additionally allows making use of results of bifurcation analysis performed on simplified homogeneous systems, thereby building on the existing body of tools and knowledge and expanding applicability and predictive power of many mathematical models. - Introduces Hidden Keystone Variable (HKV) method, which allows modeling evolution of heterogenous populations, while reducing multi-dimensional selection systems to low-dimensional systems of differential equations - Demonstrates that replicator dynamics is governed by the principle of maximal relative entropy that can be derived from the dynamics of selection systems instead of being postulated - Discusses mechanisms behind models of both Darwinian and non-Darwinian selection - Provides examples of applications to various fields, including cancer growth, global demography, population extinction, tragedy of the commons and resource sustainability, among others - Helps inform differences in underlying mechanisms of population growth from experimental observations, taking one from experiment to theory and back
Author : Xiaodong Li
Publisher : Springer Science & Business Media
ISBN 13 : 3540896937
Total Pages : 672 pages
Book Rating : 4.5/5 (48 download)
Download or read book Simulated Evolution and Learning written by Xiaodong Li and published by Springer Science & Business Media. This book was released on 2008-11-19 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 7th International Conference on Simulated Evolution and Learning, SEAL 2008, held in Melbourne, Australia, during December 7-10, 2008. The 65 papers presented were carefully reviewed and selected from 140 submissions. The topics covered are evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.
Author : Daniel Jones
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)
Download or read book Evolution and Learning in Heterogeneous Environments written by Daniel Jones and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Peter Vrancx
Publisher : Springer
ISBN 13 : 364228499X
Total Pages : 141 pages
Book Rating : 4.6/5 (422 download)
Download or read book Adaptive and Learning Agents written by Peter Vrancx and published by Springer. This book was released on 2012-02-27 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Adaptive and Learning Agents, ALA 2011, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, in May 2011. The 7 revised full papers presented together with 1 invited talk were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on single and multi-agent reinforcement learning, supervised multiagent learning, adaptation and learning in dynamic environments, learning trust and reputation, minority games and agent coordination.
Author : Zhi-Hua Zhou
Publisher : Springer
ISBN 13 : 9811359563
Total Pages : 361 pages
Book Rating : 4.8/5 (113 download)
Download or read book Evolutionary Learning: Advances in Theories and Algorithms written by Zhi-Hua Zhou and published by Springer. This book was released on 2019-05-22 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many machine learning tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Recently there have been considerable efforts to address this issue. This book presents a range of those efforts, divided into four parts. Part I briefly introduces readers to evolutionary learning and provides some preliminaries, while Part II presents general theoretical tools for the analysis of running time and approximation performance in evolutionary algorithms. Based on these general tools, Part III presents a number of theoretical findings on major factors in evolutionary optimization, such as recombination, representation, inaccurate fitness evaluation, and population. In closing, Part IV addresses the development of evolutionary learning algorithms with provable theoretical guarantees for several representative tasks, in which evolutionary learning offers excellent performance.
Author : J.D. Becker
Publisher : Springer Science & Business Media
ISBN 13 : 9783540550273
Total Pages : 540 pages
Book Rating : 4.5/5 (52 download)
Download or read book Parallelism, Learning, Evolution written by J.D. Becker and published by Springer Science & Business Media. This book was released on 1991-12-04 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the proceedings of a workshop on evolutionary models and strategies and another workshop on parallel processing, logic, organization, and technology, both held in Germany in 1989. In the search for new concepts relevant for parallel and distributed processing, the workshop on parallel processing included papers on aspects of space and time, representations of systems, non-Boolean logics, metrics, dynamics and structure, and superposition and uncertainties. The point was stressed that distributed representations of information may share features with quantum physics, such as the superposition principle and the uncertainty relations. Much of the volume contains material on general parallel processing machines, neural networks, and system-theoretic aspects. The material on evolutionary strategies is included because these strategies will yield important and powerful applications for parallel processing machines, and open the wayto new problem classes to be treated by computers.
Author :
Publisher :
ISBN 13 : 9789521015182
Total Pages : pages
Book Rating : 4.0/5 (151 download)
Download or read book Learning with Heterogeneous Expectations in an Evolutionary World written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : R. C. Bolles
Publisher : Psychology Press
ISBN 13 : 1134926456
Total Pages : 310 pages
Book Rating : 4.1/5 (349 download)
Download or read book Evolution and Learning written by R. C. Bolles and published by Psychology Press. This book was released on 2013-08-21 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: First published in 1987. Evolutionary theory and learning theory have for a long time developed in quite separate traditions. The purpose of this book is partly to celebrate new developments in the two theories by displaying some of the work of this new breed of scholar. It is the editors’ hope that they can encourage others to look more carefully at the mechanisms that make learning an evolutionary consideration and evolution a learning theory consideration.
Author : Karl S. Rosengren
Publisher : Oxford University Press
ISBN 13 : 0199909180
Total Pages : 487 pages
Book Rating : 4.1/5 (999 download)
Download or read book Evolution Challenges written by Karl S. Rosengren and published by Oxford University Press. This book was released on 2012-04-23 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: A recent poll revealed that one in four Americans believe in both creationism and evolution, while another 41% believe that creationism is true and evolution is false. A minority (only 13%) believe only in evolution. Given the widespread resistance to the idea that humans and other animals have evolved and given the attention to the ongoing debate of what should be taught in public schools, issues related to the teaching and learning of evolution are quite timely. Evolution Challenges: Integrating Research and Practice in Teaching and Learning about Evolution goes beyond the science versus religion dispute to ask why evolution is so often rejected as a legitimate scientific fact, focusing on a wide range of cognitive, socio-cultural, and motivational factors that make concepts such as evolution difficult to grasp. The volume brings together researchers with diverse backgrounds in cognitive development and education to examine children's and adults' thinking, learning, and motivation, and how aspects of representational and symbolic knowledge influence learning about evolution. The book is organized around three main challenges inherent in teaching and learning evolutionary concepts: folk theories and conceptual biases, motivational and epistemological biases, and educational aspects in both formal and informal settings. Commentaries across the three main themes tie the book together thematically, and contributors provide ideas for future research and methods for improving the manner in which evolutionary concepts are conveyed in the classroom and in informal learning experiences. Evolution Challenges is a unique text that extends far beyond the traditional evolution debate and is an invaluable resource to researchers in cognitive development, science education and the philosophy of science, science teachers, and exhibit and curriculum developers.
Author : Eran Alan Guse
Publisher :
ISBN 13 :
Total Pages : 27 pages
Book Rating : 4.:/5 (652 download)
Download or read book Learning with Heterogeneous Expectations in an Evolutionary World written by Eran Alan Guse and published by . This book was released on 2005 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Liang Feng
Publisher : Springer Nature
ISBN 13 : 3030709205
Total Pages : 144 pages
Book Rating : 4.0/5 (37 download)
Download or read book Optinformatics in Evolutionary Learning and Optimization written by Liang Feng and published by Springer Nature. This book was released on 2021-03-29 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers the recent algorithmic advances towards realizing the notion of optinformatics in evolutionary learning and optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data-driven techniques for feature engineering in automated machine learning, as well as evolutionary transfer reinforcement learning. Through reading this book, the readers will understand the concept of optinformatics, recent research progresses in this direction, as well as particular algorithm designs and application of optinformatics. Evolutionary algorithms (EAs) are adaptive search approaches that take inspiration from the principles of natural selection and genetics. Due to their efficacy of global search and ease of usage, EAs have been widely deployed to address complex optimization problems occurring in a plethora of real-world domains, including image processing, automation of machine learning, neural architecture search, urban logistics planning, etc. Despite the success enjoyed by EAs, it is worth noting that most existing EA optimizers conduct the evolutionary search process from scratch, ignoring the data that may have been accumulated from different problems solved in the past. However, today, it is well established that real-world problems seldom exist in isolation, such that harnessing the available data from related problems could yield useful information for more efficient problem-solving. Therefore, in recent years, there is an increasing research trend in conducting knowledge learning and data processing along the course of an optimization process, with the goal of achieving accelerated search in conjunction with better solution quality. To this end, the term optinformatics has been coined in the literature as the incorporation of information processing and data mining (i.e., informatics) techniques into the optimization process. The primary market of this book is researchers from both academia and industry, who are working on computational intelligence methods and their applications. This book is also written to be used as a textbook for a postgraduate course in computational intelligence emphasizing methodologies at the intersection of optimization and machine learning.
Author : Mario Giacobini
Publisher : Springer Science & Business Media
ISBN 13 : 3642290655
Total Pages : 266 pages
Book Rating : 4.6/5 (422 download)
Download or read book Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics written by Mario Giacobini and published by Springer Science & Business Media. This book was released on 2012-03-28 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2012, held in Málaga, Spain, in April 2012 co-located with the Evo* 2012 events. The 15 revised full papers presented together with 8 poster papers were carefully reviewed and selected from numerous submissions. Computational Biology is a wide and varied discipline, incorporating aspects of statistical analysis, data structure and algorithm design, machine learning, and mathematical modeling toward the processing and improved understanding of biological data. Experimentalists now routinely generate new information on such a massive scale that the techniques of computer science are needed to establish any meaningful result. As a consequence, biologists now face the challenges of algorithmic complexity and tractability, and combinatorial explosion when conducting even basic analyses.
Author : Ed Hopkins
Publisher :
ISBN 13 :
Total Pages : 13 pages
Book Rating : 4.:/5 (432 download)
Download or read book Learning and Evolution in a Heterogeneus Population written by Ed Hopkins and published by . This book was released on 1994 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yan Chen
Publisher : Springer Nature
ISBN 13 : 9811571600
Total Pages : 148 pages
Book Rating : 4.8/5 (115 download)
Download or read book Behavior and Evolutionary Dynamics in Crowd Networks written by Yan Chen and published by Springer Nature. This book was released on 2020-07-28 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a holistic framework to study behavior and evolutionary dynamics in large-scale, decentralized, and heterogeneous crowd networks. In the emerging crowd cyber-ecosystems, millions of deeply connected individuals, smart devices, government agencies, and enterprises actively interact with each other and influence each other’s decisions. It is crucial to understand such intelligent entities’ behaviors and to study their strategic interactions in order to provide important guidelines on the design of reliable networks capable of predicting and preventing detrimental events with negative impacts on our society and economy. This book reviews the fundamental methodologies to study user interactions and evolutionary dynamics in crowd networks and discusses recent advances in this emerging interdisciplinary research field. Using information diffusion over social networks as an example, it presents a thorough investigation of the impact of user behavior on the network evolution process and demonstrates how this can help improve network performance. Intended for graduate students and researchers from various disciplines, including but not limited to, data science, networking, signal processing, complex systems, and economics, the book encourages researchers in related research fields to explore the many untouched areas in this domain, and ultimately to design crowd networks with efficient, effective, and reliable services.
Author : Shu-Heng Chen
Publisher : Physica
ISBN 13 : 3790817848
Total Pages : 459 pages
Book Rating : 4.7/5 (98 download)
Download or read book Evolutionary Computation in Economics and Finance written by Shu-Heng Chen and published by Physica. This book was released on 2013-11-11 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a decade's development, evolutionary computation (EC) proves to be a powerful tool kit for economic analysis. While the demand for this equipment is increasing, there is no volume exclusively written for economists. This volume for the first time helps economists to get a quick grasp on how EC may support their research. A comprehensive coverage of the subject is given, that includes the following three areas: game theory, agent-based economic modelling and financial engineering. Twenty leading scholars from each of these areas contribute a chapter to the volume. The reader will find himself treading the path of the history of this research area, from the fledgling stage to the burgeoning era. The results on games, labour markets, pollution control, institution and productivity, financial markets, trading systems design and derivative pricing, are new and interesting for different target groups. The book also includes informations on web sites, conferences, and computer software.
