Towards Understanding Crossover for Cartesian Genetic Programming

Towards Understanding Crossover for Cartesian Genetic Programming PDF Author: Henning Cui
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Towards Understanding Crossover for Cartesian Genetic Programming

Towards Understanding Crossover for Cartesian Genetic Programming PDF Author: Henning Cui
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Cartesian Genetic Programming

Cartesian Genetic Programming PDF Author: Julian F. Miller
Publisher: Springer Science & Business Media
ISBN: 3642173101
Category : Computers
Languages : en
Pages : 358

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Book Description
Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.

Parallel Problem Solving from Nature – PPSN XVIII

Parallel Problem Solving from Nature – PPSN XVIII PDF Author: Michael Affenzeller
Publisher: Springer Nature
ISBN: 3031700554
Category :
Languages : en
Pages : 443

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Genetic Programming

Genetic Programming PDF Author: Mauro Castelli
Publisher: Springer
ISBN: 3319775537
Category : Computers
Languages : en
Pages : 331

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Book Description
This book constitutes the refereed proceedings of the 21st European Conference on Genetic Programming, EuroGP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events, EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics and applications including analysis of feature importance for metabolomics, semantic methods, evolution of boolean networks, generation of redundant features, ensembles of GP models, automatic design of grammatical representations, GP and neuroevolution, visual reinforcement learning, evolution of deep neural networks, evolution of graphs, and scheduling in heterogeneous networks.

Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2

Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2 PDF Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3030630897
Category : Technology & Engineering
Languages : en
Pages : 1015

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Book Description
This book provides the state-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research. The fifth 2020 Future Technologies Conference was organized virtually and received a total of 590 submissions from academic pioneering researchers, scientists, industrial engineers, and students from all over the world. The submitted papers covered a wide range of important topics including but not limited to computing, electronics, artificial intelligence, robotics, security and communications and their applications to the real world. After a double-blind peer review process, 210 submissions (including 6 poster papers) have been selected to be included in these proceedings. One of the meaningful and valuable dimensions of this conference is the way it brings together a large group of technology geniuses in one venue to not only present breakthrough research in future technologies, but also to promote discussions and debate of relevant issues, challenges, opportunities and research findings. The authors hope that readers find the book interesting, exciting and inspiring.

Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection

Advances in Practical Applications of Agents, Multi-Agent Systems, and Complex Systems Simulation. The PAAMS Collection PDF Author: Frank Dignum
Publisher: Springer Nature
ISBN: 3031181921
Category : Computers
Languages : en
Pages : 529

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Book Description
This book constitutes the proceedings of the 20th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2022, held in L'Aquila, Italy in July 2022. The 37 full papers in this book were reviewed and selected from 67 submissions. Another 10 demonstrations papers were selected from 11 submissions are presented here as short papers. The papers deal with the application and validation of agent-based models, methods, and technologies in a number of key applications areas, including: advanced models and learning, agent-based programming, decision-making, education and social interactions, formal and theoretic models, health and safety, mobility and the city, swarms and task allocation.

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics PDF Author: Leonardo Vanneschi
Publisher: Springer
ISBN: 3642371892
Category : Computers
Languages : en
Pages : 226

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Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.

Particle Filter

Particle Filter PDF Author: Fouad Sabry
Publisher: One Billion Knowledgeable
ISBN:
Category : Computers
Languages : en
Pages : 91

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Book Description
What is Particle Filter Particle filters, or sequential Monte Carlo methods, are a set of Monte Carlo algorithms used to find approximate solutions for filtering problems for nonlinear state-space systems, such as signal processing and Bayesian statistical inference. The filtering problem consists of estimating the internal states in dynamical systems when partial observations are made and random perturbations are present in the sensors as well as in the dynamical system. The objective is to compute the posterior distributions of the states of a Markov process, given the noisy and partial observations. The term "particle filters" was first coined in 1996 by Pierre Del Moral about mean-field interacting particle methods used in fluid mechanics since the beginning of the 1960s. The term "Sequential Monte Carlo" was coined by Jun S. Liu and Rong Chen in 1998. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Particle filter Chapter 2: Importance sampling Chapter 3: Point process Chapter 4: Fokker-Planck equation Chapter 5: Wiener's lemma Chapter 6: Klein-Kramers equation Chapter 7: Mean-field particle methods Chapter 8: Dirichlet kernel Chapter 9: Generalized Pareto distribution Chapter 10: Superprocess (II) Answering the public top questions about particle filter. (III) Real world examples for the usage of particle filter in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Particle Filter.

Machine Learning, Optimization, and Data Science

Machine Learning, Optimization, and Data Science PDF Author: Giuseppe Nicosia
Publisher: Springer Nature
ISBN: 3030375994
Category : Computers
Languages : en
Pages : 798

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Book Description
This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning, Optimization, and Data Science, LOD 2019, held in Siena, Italy, in September 2019. The 54 full papers presented were carefully reviewed and selected from 158 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Genetic Programming

Genetic Programming PDF Author: James A. Foster
Publisher: Springer
ISBN: 3540459847
Category : Computers
Languages : en
Pages : 348

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Book Description
Thisvolumerecordstheproceedingsofthe?fthEuropeanconferenceonGenetic Programming(EuroGP2002)whichtookplaceinKinsale,IrelandonApril3–5, 2002, continuing an established tradition of yearly meetings among the most prominent researchers on Genetic Programming in Europe and beyond; their proceedings have always been published in the LNCS series by Springer-Verlag. EuroGP began life in Paris in 1998 as an international workshop (April 14– 15, LNCS 1391); a second workshop took place in G ̈ oteborg in 1999 (May 26– 27, LNCS 1598). Its ?rst appearance as a conference was in the year 2000 in Edinburgh (April 15–16, LNCS 1802), followed by last year’s conference held at Lake Como (April 18–19, LNCS 2038). Since the beginning, EuroGP has been co-located with a series of specialist workshops on applications of evolutionary algorithms (LNCS 1468, 1596, 1803, and 2037). In keeping with that tradition, the EvoWorkshops were also held in Kinsale this year at the same time (LNCS 2279). Genetic Programming (GP) is a branch of Evolutionary Computation in which populations of computer programs are made to evolve and adapt to so- ing a particular problem or task by a process that draws its inspiration from Biology and Darwinian evolution. GP is a very versatile technique, which has been applied to a wide range of tasks, as a quick inspection of the 32 papers in these proceedings will easily reveal: economics, robotics, engineering, statistics, pharmacology,electronics,and?nancearebutsomeofthedomainsinwhichthey havebeenemployed.AlthoughtherateofapplicationofGPtoproblemsisst- dily growing, this conference is characterized by its concern with the theoretical foundations of GP: investigation of these issues is attaining an ever increasing depth and maturity.