Optimality In Biological And Artificial Networks

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Optimality in Biological and Artificial Networks?

Author : Daniel S. Levine
Publisher : Psychology Press
ISBN 13 : 1134786387
Total Pages : 525 pages
Book Rating : 4.1/5 (347 download)

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Book Synopsis Optimality in Biological and Artificial Networks? by : Daniel S. Levine

Download or read book Optimality in Biological and Artificial Networks? written by Daniel S. Levine and published by Psychology Press. This book was released on 2013-06-17 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural network professionals in academia and industry. The topics selected are of broad interest to both those interested in designing machines to perform intelligent functions and those interested in studying how these functions are actually performed by living organisms and generate discussion of basic and controversial issues in the study of mind. The topic of optimality was chosen because it has provoked considerable discussion and controversy in many different academic fields. There are several aspects to the issue of optimality. First, is it true that actual behavior and cognitive functions of living animals, including humans, can be considered as optimal in some sense? Second, what is the utility function for biological organisms, if any, and can it be described mathematically? Rather than organize the chapters on a "biological versus artificial" basis or by what stance they took on optimality, it seemed more natural to organize them either by what level of questions they posed or by what intelligent functions they dealt with. The book begins with some general frameworks for discussing optimality, or the lack of it, in biological or artificial systems. The next set of chapters deals with some general mathematical and computational theories that help to clarify what the notion of optimality might entail in specific classes of networks. The final section deals with optimality in the context of many different high-level issues, including exploring one's environment, understanding mental illness, linguistic communication, and social organization. The diversity of topics covered in this book is designed to stimulate interdisciplinary thinking and speculation about deep problems in intelligent system organization.

Optimality in Biological and Artificial Networks?

Author : Daniel Levine
Publisher :
ISBN 13 :
Total Pages : 528 pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Optimality in Biological and Artificial Networks? by : Daniel Levine

Download or read book Optimality in Biological and Artificial Networks? written by Daniel Levine and published by . This book was released on 2013 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural network professionals in academia and industry. The topics selected are of broad interest to both those interested in designing machines to perform intelligent functions and those interested in studying how these functions are actually performed by living organisms and generate discussion of basic and controversial issues in the study of mind. The topic of optimality was chosen because it has provoked considerable discussion and controversy in many different academic fields. There are several aspects to the issue of optimality. First, is it true that actual behavior and cognitive functions of living animals, including humans, can be considered as optimal in some sense? Second, what is the utility function for biological organisms, if any, and can it be described mathematically? Rather than organize the chapters on a "biological versus artificial" basis or by what stance they took on optimality, it seemed more natural to organize them either by what level of questions they posed or by what intelligent functions they dealt with. The book begins with some general frameworks for discussing optimality, or the lack of it, in biological or artificial systems. The next set of chapters deals with some general mathematical and computational theories that help to clarify what the notion of optimality might entail in specific classes of networks. The final section deals with optimality in the context of many different high-level issues, including exploring one's environment, understanding mental illness, linguistic communication, and social organization. The diversity of topics covered in this book is designed to stimulate interdisciplinary thinking and speculation about deep problems in intelligent system organization.

Advanced Optimal Control and Applications Involving Critic Intelligence

Author : Ding Wang
Publisher : Springer Nature
ISBN 13 : 9811972915
Total Pages : 283 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Optimal Control and Applications Involving Critic Intelligence by : Ding Wang

Download or read book Advanced Optimal Control and Applications Involving Critic Intelligence written by Ding Wang and published by Springer Nature. This book was released on 2023-01-21 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to report new optimal control results with critic intelligence for complex discrete-time systems, which covers the novel control theory, advanced control methods, and typical applications for wastewater treatment systems. Therein, combining with artificial intelligence techniques, such as neural networks and reinforcement learning, the novel intelligent critic control theory as well as a series of advanced optimal regulation and trajectory tracking strategies are established for discrete-time nonlinear systems, followed by application verifications to complex wastewater treatment processes. Consequently, developing such kind of critic intelligence approaches is of great significance for nonlinear optimization and wastewater recycling. The book is likely to be of interest to researchers and practitioners as well as graduate students in automation, computer science, and process industry who wish to learn core principles, methods, algorithms, and applications in the field of intelligent optimal control. It is beneficial to promote the development of intelligent optimal control approaches and the construction of high-level intelligent systems.

Neural Network Exploration Using Optimal Experiment Design

Author : David A. Cohn
Publisher :
ISBN 13 :
Total Pages : 11 pages
Book Rating : 4.:/5 (31 download)

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Book Synopsis Neural Network Exploration Using Optimal Experiment Design by : David A. Cohn

Download or read book Neural Network Exploration Using Optimal Experiment Design written by David A. Cohn and published by . This book was released on 1994 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence Technologies for Computational Biology

Author : Ranjeet Kumar Rout
Publisher : CRC Press
ISBN 13 : 1000778681
Total Pages : 345 pages
Book Rating : 4.0/5 (7 download)

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Book Synopsis Artificial Intelligence Technologies for Computational Biology by : Ranjeet Kumar Rout

Download or read book Artificial Intelligence Technologies for Computational Biology written by Ranjeet Kumar Rout and published by CRC Press. This book was released on 2022-11-10 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: • Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. • Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. • Presents the application of evolutionary computations for fractal visualization of sequence data. • Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. • Examines the roles of efficient computational techniques in biology.

Artificial Neural Networks: Biological Inspirations – ICANN 2005

Author : Wlodzislaw Duch
Publisher : Springer
ISBN 13 : 354028754X
Total Pages : 718 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Artificial Neural Networks: Biological Inspirations – ICANN 2005 by : Wlodzislaw Duch

Download or read book Artificial Neural Networks: Biological Inspirations – ICANN 2005 written by Wlodzislaw Duch and published by Springer. This book was released on 2007-05-22 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005), held on September 11–15, 2005 in Warsaw, Poland, with several accompanying workshops held on September 15, 2005 at the Nicolaus Copernicus University, Toru , Poland. The ICANN conference is an annual meeting organized by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society, and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in those fields. In 2005 the ICANN conference was organized by the Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland, and the Nicolaus Copernicus Univ- sity, Toru , Poland. From over 600 papers submitted to the regular sessions and some 10 special c- ference sessions, the International Program Committee selected – after a thorough peer-review process – about 270 papers for publication. The large number of papers accepted is certainly a proof of the vitality and attractiveness of the field of artificial neural networks, but it also shows a strong interest in the ICANN conferences.

Artificial Neural Networks in Medicine and Biology

Author : H. Malmgren
Publisher : Springer Science & Business Media
ISBN 13 : 1447105133
Total Pages : 339 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Artificial Neural Networks in Medicine and Biology by : H. Malmgren

Download or read book Artificial Neural Networks in Medicine and Biology written by H. Malmgren and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. Forty-two contributions were accepted for presentation; in addition to these, S invited papers are also included. Research within medicine and biology has often been characterised by application of statistical methods for evaluating domain specific data. The growing interest in Artificial Neural Networks has not only introduced new methods for data analysis, but also opened up for development of new models of biological and ecological systems. The ANNIMAB-l conference is focusing on some of the many uses of artificial neural networks with relevance for medicine and biology, specifically: • Medical applications of artificial neural networks: for better diagnoses and outcome predictions from clinical and laboratory data, in the processing of ECG and EEG signals, in medical image analysis, etc. More than half of the contributions address such clinically oriented issues. • Uses of ANNs in biology outside clinical medicine: for example, in models of ecology and evolution, for data analysis in molecular biology, and (of course) in models of animal and human nervous systems and their capabilities. • Theoretical aspects: recent developments in learning algorithms, ANNs in relation to expert systems and to traditional statistical procedures, hybrid systems and integrative approaches.

Optimal Design of Complex Mechanical Systems

Author : Giampiero Mastinu
Publisher : Springer Science & Business Media
ISBN 13 : 3540343555
Total Pages : 359 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Optimal Design of Complex Mechanical Systems by : Giampiero Mastinu

Download or read book Optimal Design of Complex Mechanical Systems written by Giampiero Mastinu and published by Springer Science & Business Media. This book was released on 2007-07-20 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents foundations and practical application of multi-objective optimization methods to Vehicle Design Problems, bolstered with an extensive collection of examples. Opening with a broad theoretical introduction to the optimization of complex mechanical systems and multi-objective optimization methods, the book presents several applications which are extensively exposed here for the first time. The book includes examples of proposed methods to the solution of real vehicle design problems.

Artificial Neural Networks

Author : Petia Koprinkova-Hristova
Publisher : Springer
ISBN 13 : 3319099035
Total Pages : 487 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Artificial Neural Networks by : Petia Koprinkova-Hristova

Download or read book Artificial Neural Networks written by Petia Koprinkova-Hristova and published by Springer. This book was released on 2014-09-02 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.

Plausible Neural Networks for Biological Modelling

Author : H.A. Mastebroek
Publisher : Springer Science & Business Media
ISBN 13 : 9401006741
Total Pages : 264 pages
Book Rating : 4.4/5 (1 download)

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Book Synopsis Plausible Neural Networks for Biological Modelling by : H.A. Mastebroek

Download or read book Plausible Neural Networks for Biological Modelling written by H.A. Mastebroek and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence, they are suitable for performing straightforward and relatively simple tasks like classification, pattern recognition and prediction, as well as more sophisticated tasks like the processing of temporal sequences and the context dependent processing of complex problems. Also, a wide variety of control tasks can be executed by them, and the suggestion is relatively obvious that neural networks perform adequately in such cases because they are thought to mimic the biological nervous system which is also devoted to such tasks. As we shall see, this suggestion is false but does not do any harm as long as it is only the final performance of the algorithm which counts. Neural networks are also used in the modelling of the functioning of (sub systems in) the biological nervous system. It will be clear that in such cases it is certainly not irrelevant how similar their algorithm is to what is precisely going on in the nervous system. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies).

Artificial Intelligence for Biology and Agriculture

Author : S. Panigrahi
Publisher : Springer Science & Business Media
ISBN 13 : 9401150486
Total Pages : 258 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Artificial Intelligence for Biology and Agriculture by : S. Panigrahi

Download or read book Artificial Intelligence for Biology and Agriculture written by S. Panigrahi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two general articles on robotics and fuzzy logic. The article on robotics focuses on the application of robotics technology in plant production. The second article on fuzzy logic provides a general overview of the basics of fuzzy logic and a typical agricultural application of fuzzy logic. The article `End effectors for tomato harvesting' enhances further the robotic research as applied to tomato harvesting. The application of computer vision techniques for different biological/agricultural applications, for example, length determination of cheese threads, recognition of plankton images and morphological identification of cotton fibers, depicts the complexity and heterogeneities of the problems and their solutions. The development of a real-time orange grading system in the article `Video grading of oranges in real-time' further reports the capability of computer vision technology to meet the demand of high quality food products. The integration of neural network technology with computer vision and fuzzy logic for defect detection in eggs and identification of lettuce growth shows the power of hybridization of AI technologies to solve agricultural problems. Additional papers also focus on automated modeling of physiological processes during postharvest distribution of agricultural products, the applications of neural networks, fusion of AI technologies and three dimensional computer vision technologies for different problems ranging from botanical identification and cell migration analysis to food microstructure evaluation.

Neural Networks

Author : Raul Rojas
Publisher : Springer Science & Business Media
ISBN 13 : 3642610684
Total Pages : 511 pages
Book Rating : 4.6/5 (426 download)

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Book Synopsis Neural Networks by : Raul Rojas

Download or read book Neural Networks written by Raul Rojas and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.

Optimal Event-Triggered Control Using Adaptive Dynamic Programming

Author : Sarangapani Jagannathan
Publisher : CRC Press
ISBN 13 : 1040049168
Total Pages : 348 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Optimal Event-Triggered Control Using Adaptive Dynamic Programming by : Sarangapani Jagannathan

Download or read book Optimal Event-Triggered Control Using Adaptive Dynamic Programming written by Sarangapani Jagannathan and published by CRC Press. This book was released on 2024-06-21 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal Event-triggered Control using Adaptive Dynamic Programming discusses event triggered controller design which includes optimal control and event sampling design for linear and nonlinear dynamic systems including networked control systems (NCS) when the system dynamics are both known and uncertain. The NCS are a first step to realize cyber-physical systems (CPS) or industry 4.0 vision. The authors apply several powerful modern control techniques to the design of event-triggered controllers and derive event-trigger condition and demonstrate closed-loop stability. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included for each case. The book begins by providing background on linear and nonlinear systems, NCS, networked imperfections, distributed systems, adaptive dynamic programming and optimal control, stability theory, and optimal adaptive event-triggered controller design in continuous-time and discrete-time for linear, nonlinear and distributed systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for infinite horizons. The text then: Introduces event triggered control of linear and nonlinear systems, describing the design of adaptive controllers for them Presents neural network-based optimal adaptive control and game theoretic formulation of linear and nonlinear systems enclosed by a communication network Addresses the stochastic optimal control of linear and nonlinear NCS by using neuro dynamic programming Explores optimal adaptive design for nonlinear two-player zero-sum games under communication constraints to solve optimal policy and event trigger condition Treats an event-sampled distributed linear and nonlinear systems to minimize transmission of state and control signals within the feedback loop via the communication network Covers several examples along the way and provides applications of event triggered control of robot manipulators, UAV and distributed joint optimal network scheduling and control design for wireless NCS/CPS in order to realize industry 4.0 vision An ideal textbook for senior undergraduate students, graduate students, university researchers, and practicing engineers, Optimal Event Triggered Control Design using Adaptive Dynamic Programming instills a solid understanding of neural network-based optimal controllers under event-sampling and how to build them so as to attain CPS or Industry 4.0 vision.

Networks in Systems Biology

Author : Fabricio Alves Barbosa da Silva
Publisher : Springer Nature
ISBN 13 : 3030518620
Total Pages : 381 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Networks in Systems Biology by : Fabricio Alves Barbosa da Silva

Download or read book Networks in Systems Biology written by Fabricio Alves Barbosa da Silva and published by Springer Nature. This book was released on 2020-10-03 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.

Index of Conference Proceedings

Author : British Library. Document Supply Centre
Publisher :
ISBN 13 :
Total Pages : 938 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Index of Conference Proceedings by : British Library. Document Supply Centre

Download or read book Index of Conference Proceedings written by British Library. Document Supply Centre and published by . This book was released on 1997 with total page 938 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Intelligent Computing in Optimal Design

Author : Tadeusz Burczyński
Publisher : Springer Nature
ISBN 13 : 3030341615
Total Pages : 245 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Intelligent Computing in Optimal Design by : Tadeusz Burczyński

Download or read book Intelligent Computing in Optimal Design written by Tadeusz Burczyński and published by Springer Nature. This book was released on 2020-01-01 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is devoted to intelligent design of structures as a novel kind of designing based on computational intelligence. The proposed methodology based on computational intelligence has some heuristic and learning attributes typical for natural intelligence. Computer models of the structures are built on the base of the finite element method (FEM), the boundary element method (BEM) or coupling of FEM and BEM. The short description of possible discrete models of structures using these methods is included in the Chapter 2. Various kinds of intelligent approaches using sequential, parallel, distributed, fuzzy and hybrid evolutionary, immune and particle swarm algorithms and neural computing are presented in Chapter 3. Different kinds of optimization such as shape, topology, size and material optimization for structures under static and dynamical mechanical and thermo-mechanical loadings, structures with cracks and composite structures are considered in Chapter 4. Multi-objective optimization for coupled problems is also taken into account. Several numerical examples illustrating these kinds of optimization are presented for 2-D (plane-stress or plane-strain, plates, shells) as well as 3-D structures. Chapter 5 is devoted to special problems related to solving inverse problems in which boundary conditions, defects such as voids or cracks and material characteristics, are unknown. Closing comments summarizing the book are presented in Chapter 6.

Combining Artificial Neural Nets

Author : Amanda J.C. Sharkey
Publisher : Springer Science & Business Media
ISBN 13 : 1447107934
Total Pages : 300 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Combining Artificial Neural Nets by : Amanda J.C. Sharkey

Download or read book Combining Artificial Neural Nets written by Amanda J.C. Sharkey and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.