The book consists of 29 chapters which have been selected and invited from the submissions to the 1st International Conference on Collective intelligence - Semantic Web, Social Networks & Multiagent Systems (ICCCI...
ISBN:
(数字)9783642039584
ISBN:
(纸本)9783642039577
The book consists of 29 chapters which have been selected and invited from the submissions to the 1st International Conference on Collective intelligence - Semantic Web, Social Networks & Multiagent Systems (ICCCI 2009). All chapters in the book discuss various examples of applications of computational collective intelligence and related technologies to such fields as semantic web, information systems ontologies, social networks, agent and multiagent systems. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants to courses on Soft Computing, Multi-Agent Systems and Robotics. This book can also be useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases intelligent collectives. Many such challenges are suggested by particular approaches and models presented in particular chapters of this book.
The decision to invest in oil field development is an extremely complex problem, even in the absence of uncertainty, due to the great number of technological alternatives that may be used, to the dynamic complexity of...
ISBN:
(数字)9783540930006
ISBN:
(纸本)9783540929994
The decision to invest in oil field development is an extremely complex problem, even in the absence of uncertainty, due to the great number of technological alternatives that may be used, to the dynamic complexity of oil reservoirs - which involves multiphase flows (oil, gas and water) in porous media with phase change, and to the complicated combinatorial optimization problem of choosing the optimal oil well network, that is, choosing the number and types of wells (horizontal, vertical, directional, multilateral) required for draining oil from a field with a view to maximizing its economic value. The present book is a result of about 4 years of research in this area through a partnership between the Applied computationalintelligence Laboratory (ICA) of the Department of Electrical Engineering at PUC-Rio, and Petrobras, through its R&D (research and development) program called PRAVAP (Advanced Oil Recovery Program), which is linked to its research center (CENPES). The book makes use of computationalintelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy systems for purposes of solving this investment under uncertainty problem. These techniques are combined with modern finance theory, particularly with the real options theory, also known as the investment under uncertainty theory, in such a way as to provide practical as well as theoretically rigorous solutions. This partnership, through which countless master's and doctoral theses were produced at PUC-Rio and computational methodologies and programs were developed for Petrobras, has been summarized in this original and comprehensive work, now available to a wider audience of researchers and interested readers.
Pervasive computing devices are able to generate enormous amounts of distributed data, from which knowledge about situations and facts occurring in the world should be inferred for the use of pervasive services. Howev...
详细信息
ISBN:
(纸本)9781424453313
Pervasive computing devices are able to generate enormous amounts of distributed data, from which knowledge about situations and facts occurring in the world should be inferred for the use of pervasive services. However accessing and managing effectively such a huge amount of distributed information is challenging for services. In this paper we propose a self-organized agent-based approach to autonomously organize distributed contextual data items into sorts of knowledge networks. Knowledge networks are conceived as an alive self-organized layer in charge of managing data, that can facilitate services in extracting useful information out of a large amount of distributed items. We present the W4 Data Model we used to represent data and the self-organized approach to build Knowledge Networks. Some experimental results are reported to support our arguments and proposal.
This book is the result of a successful special session on constraint-handling techniques used in evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007, with the aim of putting together...
详细信息
ISBN:
(数字)9783642006197
ISBN:
(纸本)9783642006180
This book is the result of a successful special session on constraint-handling techniques used in evolutionary algorithms within the Congress on Evolutionary Computation (CEC) in 2007, with the aim of putting together recent studies on constrained numerical optimization using evolutionary algorithms and other bio-inspired approaches. The book covers six main topics: The first two chapters refer to swarm- intelligence-based approaches. Differential evolution, a very competitive evolutionary algorithm for constrained optimization, is studied in the next three chapters. Two different constraint-handling techniques for evolutionary multiobjective optimization are presented in the two subsequent chapters. Two hybrid approaches, one with a combination of two nature-inspired heuristics and the other with the mix of a genetic algorithm and a local search operator, are detailed in the next two chapters. Finally, a constraint-handling technique designed for a real-world problem and a survey on artificial immune system in constrained optimization are the subjects of the final two chapters. The intended audience for this book comprises graduate students, practitioners and researchers interested on alternative techniques to solve numerical optimization problems in presence of constraints.
The following chapters of this book presents key issues concerning the neurophysiological aspects of executing cognitive thought processes and the basics of cognitive informatics and new proposals of UBIAS systems ded...
ISBN:
(数字)9783642026935
ISBN:
(纸本)9783642026928
The following chapters of this book presents key issues concerning the neurophysiological aspects of executing cognitive thought processes and the basics of cognitive informatics and new proposals of UBIAS systems dedicated to the meaning-based analysis of selected types of medical images. In particular, to structure the considerations of pattern classification methods, Chapter 2 discusses traditional image recognition techniques and algorithms from the simplest methods based on metric spaces up to methods that use the paradigms of computer image understanding. Chapter 3 deals with the cognitive aspects of brain function. Information from this chapter allows the authors, in a latter part of this book, to show functional analogies between the operation of biological systems and computer implementations. Chapter 4 provides a short compendium of knowledge about the new branch of informatics which formally describes thought processes, namely cognitive informatics. The introduction to subjects of cognitive processes analysed by cognitive informatics will then allow us to introduce new classes of computer systems executing cognitive resonance processes. The following Chapter 5 defines a new class of information systems using cognitive resonance processes. This chapter reviews several proposals of various classes of cognitive categorisation systems put forward by the authors. Chapter 6 contains a broader discussion of the UBIAS system class which the authors proposed for the meaning-based analysis of medical images. Then, Chapter 7 discusses in detail two examples of UBIAS systems built for the semantic classification of foot bone X-rays and images of long bone injuries in extremities. Chapter 8, the last, compiles and summarises information on creating cognitive vision systems designed for the semantic classification of patterns. The authors present this book to Readers in the hope that it will stir their fascination with the scientific aspects of creating new generation
The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this ...
ISBN:
(数字)9783540880516
ISBN:
(纸本)9783540880509
The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design. This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.
The book is a collection of invited papers on Constructive methods for Neural networks. Most of the chapters are extended versions of works presented on the special session on constructive neural network algorithms of...
ISBN:
(数字)9783642045127
ISBN:
(纸本)9783642045110
The book is a collection of invited papers on Constructive methods for Neural networks. Most of the chapters are extended versions of works presented on the special session on constructive neural network algorithms of the 18th International Conference on Artificial Neural Networks (ICANN 2008) held September 3-6, 2008 in Prague, Czech Republic. The book is devoted to constructive neural networks and other incremental learning algorithms that constitute an alternative to standard trial and error methods for searching adequate architectures. It is made of 15 articles which provide an overview of the most recent advances on the techniques being developed for constructive neural networks and their applications. It will be of interest to researchers in industry and academics and to post-graduate students interested in the latest advances and developments in the field of artificial neural networks.
暂无评论