Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2008) PDF Author: Natalio Krasnogor
Publisher: Springer Science & Business Media
ISBN: 3642032109
Category : Technology & Engineering
Languages : en
Pages : 320

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Book Description
The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the arti?cial neuron given by McCulloch and Pitts was inspired from biological observations of neural mechanisms; the power of evolution in nature in the diverse species that make up our world has been related to a particular form of problem solving based on the idea of survival of the ?ttest; similarly, - ti?cial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The ?rst and second editions of the International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), were held in Granada, Spain, 2006, and in Acireale, Italy, 2007, respectively. As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum were the latest ideas and state of the art research related to nature inspired cooperative strategies for problem solving were discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributionsincludenature-inspiredtechniqueslikeGeneticAlgorithms,Ant Colonies, Amorphous Computing, Arti?cial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2008)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2008) PDF Author: Natalio Krasnogor
Publisher: Springer Science & Business Media
ISBN: 3642032109
Category : Technology & Engineering
Languages : en
Pages : 320

Get Book Here

Book Description
The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the arti?cial neuron given by McCulloch and Pitts was inspired from biological observations of neural mechanisms; the power of evolution in nature in the diverse species that make up our world has been related to a particular form of problem solving based on the idea of survival of the ?ttest; similarly, - ti?cial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The ?rst and second editions of the International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), were held in Granada, Spain, 2006, and in Acireale, Italy, 2007, respectively. As in these two previous editions, the aim of NICSO 2008, held in Tenerife, Spain, was to provide a forum were the latest ideas and state of the art research related to nature inspired cooperative strategies for problem solving were discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributionsincludenature-inspiredtechniqueslikeGeneticAlgorithms,Ant Colonies, Amorphous Computing, Arti?cial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2011) PDF Author: David Alejandro Pelta
Publisher: Springer
ISBN: 3642240941
Category : Technology & Engineering
Languages : en
Pages : 359

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Book Description
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. The previous editions of NICSO were held in Granada, Spain (2006), Acireale, Italy (2007), Tenerife, Spain (2008), and again in Granada in 2010. NICSO evolved to be one of the most interesting and profiled workshops in nature inspired computing. NICSO 2011 has offered an inspiring environment for debating the state of the art ideas and techniques in nature inspired cooperative strategies and a comprehensive image on recent applications of these ideas and techniques. The topics covered by this volume include Swarm Intelligence (such as Ant and Bee Colony Optimization), Genetic Algorithms, Multiagent Systems, Coevolution and Cooperation strategies, Adversarial Models, Synergic Building Blocks, Complex Networks, Social Impact Models, Evolutionary Design, Self Organized Criticality, Evolving Systems, Cellular Automata, Hybrid Algorithms, and Membrane Computing (P-Systems).

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) PDF Author: Carlos Cruz
Publisher: Springer
ISBN: 3642125387
Category : Technology & Engineering
Languages : en
Pages : 401

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Book Description
Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2013) PDF Author: German Terrazas
Publisher: Springer
ISBN: 331901692X
Category : Technology & Engineering
Languages : en
Pages : 357

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Book Description
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm Intelligence, Hyper-heuristics, Evolutionary Algorithms, Cellular Automata, Artificial Bee Colony, Dynamic Optimization, Support Vector Machines, Multi-Agent Systems, Ant Clustering, Evolutionary Design Optimisation, Game Theory and other several Cooperation Models.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007) PDF Author: Natalio Krasnogor
Publisher: Springer Science & Business Media
ISBN: 3540789863
Category : Computers
Languages : en
Pages : 520

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Book Description
Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2007) PDF Author: Natalio Krasnogor
Publisher: Springer
ISBN: 3540789871
Category : Computers
Languages : en
Pages : 520

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Book Description
Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) PDF Author: Carlos Cruz
Publisher: Springer Science & Business Media
ISBN: 3642125379
Category : Computers
Languages : en
Pages : 401

Get Book Here

Book Description
Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.

Nature-Inspired Algorithms and Applied Optimization

Nature-Inspired Algorithms and Applied Optimization PDF Author: Xin-She Yang
Publisher: Springer
ISBN: 3319676695
Category : Technology & Engineering
Languages : en
Pages : 332

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Book Description
This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Intelligent Computer Graphics 2009

Intelligent Computer Graphics 2009 PDF Author: Dimitri Plemenos
Publisher: Springer
ISBN: 3642034527
Category : Technology & Engineering
Languages : en
Pages : 228

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Book Description
The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volume “Artificial Int- ligence Techniques for Computer Graphics”. Nowadays, intelligent techniques are more and more used in Computer Graphics in order, not only to optimise the pr- essing time, but also to find more accurate solutions for a lot of Computer Gra- ics problems, than with traditional methods. What are intelligent techniques for Computer Graphics? Mainly, they are te- niques based on Artificial Intelligence. So, problem resolution (especially constraint satisfaction) techniques, as well as evolutionary techniques, are used in Declarative scene Modelling; heuristic search techniques, as well as strategy games techniques, are currently used in scene understanding and in virtual world exploration; multi-agent techniques and evolutionary algorithms are used in behavioural animation; and so on. However, even if in most cases the used intelligent techniques are due to Artificial - telligence, sometimes, simple human intelligence can find interesting solutions in cases where traditional Computer Graphics techniques, even combined with Artificial Intelligence ones, cannot propose any satisfactory solution. A good example of such a case is the one of scene understanding, in the case where several parts of the scene are impossible to access.

Non-Standard Parameter Adaptation for Exploratory Data Analysis

Non-Standard Parameter Adaptation for Exploratory Data Analysis PDF Author: Wesam Ashour Barbakh
Publisher: Springer
ISBN: 3642040055
Category : Computers
Languages : en
Pages : 231

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Book Description
Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variations thereof. In this book, we first lay the groundwork by reviewing some standard clustering algorithms and projection algorithms before presenting various non-standard criteria for clustering. The family of algorithms developed are shown to perform better than the standard clustering algorithms on a variety of datasets. We then consider extensions of the basic mappings which maintain some topology of the original data space. Finally we show how reinforcement learning can be used as a clustering mechanism before turning to projection methods. We show that several varieties of reinforcement learning may also be used to define optimal projections for example for principal component analysis, exploratory projection pursuit and canonical correlation analysis. The new method of cross entropy adaptation is then introduced and used as a means of optimising projections. Finally an artificial immune system is used to create optimal projections and combinations of these three methods are shown to outperform the individual methods of optimisation.