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Soft computing techniques have reached a significant level of recognition and - ceptance from both the academic and industrial communities. The papers collected in this volume illustrate the depth of the current theoretical research trends and the breadth of the application areas in which soft computing methods are making c- tributions. This volume consists of forty six selected papers presented at the Fourth Inter- tional Conference on Recent Advances in Soft Computing, which was held in N- th th tingham, United Kingdom on 12 and 13 December 2002 at Nottingham Trent University. This volume is organized in five parts. The first four parts address mainly the f- damental and theoretical advances in soft computing, namely Artificial Neural Networks, Evolutionary Computing, Fuzzy Systems and Hybrid Systems. The fifth part of this volume presents papers that deal with practical issues and ind- trial applications of soft computing techniques. We would like to express our sincere gratitude to all the authors who submitted contributions for inclusion. We are also indebted to Janusz Kacprzyk for his - vices related to this volume. We hope you find the volume an interesting refl- tion of current theoretical and application based soft computing research.

This Festschrift volume is published in honor of Takao Terano on the occasion of his retirement. Takao Terano is a leading expert in the areas of agent-based modelling, knowledge systems, evolutionary computation, and service science.The contributions in this volume reflect the breadth and impact of his work. The volume contains 12 full papers related to Takao Terano's research. They deal with various aspects of artificial intelligence, multi-agent systems, collaborative and social computing, social networks, ubiquitous computing.

This book constitutes the refereed proceedings of the 9th Dortmund Fuzzy Days, held in Dortmund, Germany, 2006. The Fuzzy Days conference has established itself as an international forum for the discussion of new results in the field of Computational Intelligence. All the papers had to undergo a thorough review guaranteeing a solid quality of the programme. The papers are devoted to foundational and practical issues in fuzzy systems, neural networks, evolutionary algorithms, and machine learning and thus cover the whole range of computational intelligence.

ISDA'03 General Chair's Message On behalf of the ISDA'03 organizing committee, I wish to extend a very warm welcome to the conference and Tulsa in August 2003. The conference program committee has organized an exciting and invigorating program comprising pres­ entations from distinguished experts in the field, and important and wide-ranging contributions on state-of-the-art research that provide new insights into'Current Innovations in Intelligent Systems Design and Applications'. ISDA'03 builds on the success of last years. ISDA'02 was held in Atlanta, USA, August 07-08,2002 and attracted participants from over 25 countries. ISDA'03, the Third International Conference on Intelligent Systems Design and Applications, held during August 10-13, 2003, in Tulsa, USA presents a rich and exciting program. The main themes addressed by this conference are: Architectures of intelligent systems Image, speech and signal processing Internet modeling Data mining Business and management applications Control and automation Software agents Knowledge management ISDA'03 is hosted by the College of Arts and Sciences, Oklahoma State Univer­ sity, USA. ISDA'03 is technically sponsored by IEEE Systems Man and Cyber­ netics Society, World Federation on Soft Computing, European Society for Fuzzy Logic and Technology, Springer Verlag- Germany, Center of Excellence in In­ formation Technology and Telecommunications (COEITT) and Oklahoma State University. ISDA'03 received 117 technical paper submissions from over 28 countries, 7 tutorials, 3 special technical sessions and 1 workshop proposal.

This volume presents state-of-the-art complementarity applications, algorithms, extensions and theory in the form of eighteen papers. These at the International Conference on Com­ invited papers were presented plementarity 99 (ICCP99) held in Madison, Wisconsin during June 9-12, 1999 with support from the National Science Foundation under Grant DMS-9970102. Complementarity is becoming more widely used in a variety of appli­ cation areas. In this volume, there are papers studying the impact of complementarity in such diverse fields as deregulation of electricity mar­ kets, engineering mechanics, optimal control and asset pricing. Further­ more, application of complementarity and optimization ideas to related problems in the burgeoning fields of machine learning and data mining are also covered in a series of three articles. In order to effectively process the complementarity problems that arise in such applications, various algorithmic, theoretical and computational extensions are covered in this volume. Nonsmooth analysis has an im­ portant role to play in this area as can be seen from articles using these tools to develop Newton and path following methods for constrained nonlinear systems and complementarity problems. Convergence issues are covered in the context of active set methods, global algorithms for pseudomonotone variational inequalities, successive convex relaxation and proximal point algorithms. Theoretical contributions to the connectedness of solution sets and constraint qualifications in the growing area of mathematical programs with equilibrium constraints are also presented. A relaxation approach is given for solving such problems. Finally, computational issues related to preprocessing mixed complementarity problems are addressed.

Cooperation is pervasive throughout nature, but its origin remains an open question. For decades, social scientists, business leaders, and economists have struggled with an important question: why is cooperation so ubiquitous among unrelated humans? The answers would have profound effects because anything that promotes cooperation leads to more productive work environments and benefits society at large. Game theory provides an ideal framework for studying social dilemmas, or those situations in which people decide whether to cooperate with others (benefitting the group) or defect by prioritizing their self-interest (benefitting only the individual). The social dilemma is formulated as a mathematical game and then programmed into a computer model. Simulating the game allows researchers to investigate potential theories to explain how cooperation emerges and what promotes its persistence. Over the past 25 years, countless papers on social dilemma games have been published, yet arguably little progress has been made. The problem is the social dilemma game models are unrealistic in the sense they contain artificial constructs that deviate from the way humans act. This book describes the shortcomings in current social dilemma game modeling techniques and provides guidance on designing more effective models. A basic introduction to game theory is provided with an emphasis on the prisoner's dilemma, the most widely studied social dilemma game. Individual chapters are provided detailing the shortcomings of weak selection, spatial games, and the Moran process. Computer model validation is also discussed at length. The recommendations found in this book should help design more realistic social dilemma game models likely to produce a better understanding of human cooperation.

This volume is a collection of papers presented at the international conference on Nonlinear Mathematics for Uncertainty and Its Applications (NLMUA2011), held at Beijing University of Technology during the week of September 7--9, 2011. The conference brought together leading researchers and practitioners involved with all aspects of nonlinear mathematics for uncertainty and its applications.Over the last fifty years there have been many attempts in extending the theory of classical probability and statistical models to the generalized one which can cope with problems of inference and decision making when the model-related information is scarce, vague, ambiguous, or incomplete. Such attempts include the study of nonadditive measures and their integrals, imprecise probabilities and random sets, and their applications in information sciences, economics, finance, insurance, engineering, and social sciences.The book presents topics including nonadditive measures and nonlinear integrals, Choquet, Sugeno and other types of integrals, possibility theory, Dempster-Shafer theory, random sets, fuzzy random sets and related statistics, set-valued and fuzzy stochastic processes, imprecise probability theory and related statistical models, fuzzy mathematics, nonlinear functional analysis, information theory, mathematical finance and risk managements, decision making under various types of uncertainty, and others.

Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments.'Soft Computing in Industrial Applications'contains a collection of papers that were presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.

Hybrid Artificial Intelligence Systems (HAIS) combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on'Hybrid Artificial Intelligence Systems'contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain. This carefully edited book provides a comprehensive overview of the recent advances in the hybrid intelligent systems and covers a wide range of application areas, including data analysis and data mining, intelligent control, pattern recognition, robotics, optimization, etc. The book is aimed at researchers, practitioners and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solving real-world problems.

Evolving agents to play games is a promising technology. It can provide entertaining opponents for games like Chess or Checkers, matched to a human opponent as an alternative to the perfect and unbeatable opponents embodied by current artifical intelligences. Evolved agents also permit us to explore the strategy space of mathematical games like Prisoner's Dilemma and Rock-Paper-Scissors. This book summarizes, explores, and extends recent work showing that there are many unsuspected factors that must be controlled in order to create a plausible or useful set of agents for modeling cooperation and conflict, deal making, or other social behaviors. The book also provides a proposal for an agent training protocol that is intended as a step toward being able to train humaniform agents—in other words, agents that plausibly model human behavior.

The series of Online World Conferences on Soft Computing (WSC) is organized by the World Federation of Soft Computing (WFSC) and has become an established annual event in the academic calendar and was already held for the 8th time in 2003. Starting as a small workshop held at Nagoya University, Japan in 1994 it has - tured to the premier online event on soft computing in industrial applications. It has been hosted by the universities of Granada, Spain, Fraunhofer Gesellschaft, Berlin, Cran?eld University, Helsinki University of Technology and Nagoya University. The goal of WFSC is to promote soft computing across the world, by using the internet as a forum for virtual technical discussion and publishing at no cost to authors and participants. The of?cial journal of the World Federation on Soft Computing is the journal Applied Soft Computing. The 8th WSC Conference (WSC8) took place from September 29th to October 10th, 2003. Registered participants had the opportunity to follow and discuss the online presentations of authors from all over the world. Out of more than 60 subm- sions the program committee had accepted 27 papers for?nal presentation at WSC8.

This book, which goes far beyond a traditional collection of technical articles, is dedicated to Enric Trillas, a fuzzy systems pioneer but also an internationally renowned researcher in other areas of science, such as mathematics and aerospace, and an outstanding manager of scientific affairs in Spain. Some of the contributions in this book develop technical, state-of-the-art themes obviously related to fuzzy logic, while others resemble popular-science articles that shed light on complex mathematical concepts. There are also chapters that highlight the authors'personal relationships and experiences working with Enric Trillas. While planning this book project, the editors decided to give contributors absolute freedom of thought and expression in preparing their chapters. The result is a colorful and inspiring mixture of styles and topics, which perfectly reflects Enric Trillas's multifaceted contributions to research and his outstanding role in promoting education and technological transfer in the field of soft computing. This Festschrift to Enric Trillas, published on the occasion of his 75th birthday, is not only intended as an exemplary source of information for young scientists dealing with uncertainty, imprecision and accuracy of models, but also as an inspiring guide to the role of scientists in education, politics and communication.

The analysis of experimental data resulting from some underlying random process is a fundamental part of most scientific research. Probability Theory and Statistics have been developed as flexible tools for this analyis, and have been applied successfully in various fields such as Biology, Economics, Engineering, Medicine or Psychology. However, traditional techniques in Probability and Statistics were devised to model only a singe source of uncertainty, namely randomness. In many real-life problems randomness arises in conjunction with other sources, making the development of additional'softening'approaches essential. This book is a collection of papers presented at the 2nd International Conference on Soft Methods in Probability and Statistics (SMPS'2004) held in Oviedo, providing a comprehensive overview of the innovative new research taking place within this emerging field.

This book represents the combined peer-reviewed proceedings of the Fourth International Symposium on Intelligent Distributed Computing -- IDC 2010 and of the Second International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS'2010. Both events were held in Tangier, Morocco during September 16-18, 2010. The 33 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: agent-based e-business, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, distributed algorithms, distributed data mining, distributed simulation, grid computing, image processing, information extraction, knowledge management, logic programming, mobile agents, ontologies, pervasive computing, Petri nets, process modeling, self-organizing systems, semantic web services, service oriented computing, social networks and trust, swarm intelligence, web applications, wireless sensor networks.

Intelligent computing is becoming a mature?eld of information and communication technology, covering a hybrid palette of methods and techniques derived from clas- cal arti?cial intelligence, computational intelligence, multi-agent systems etc. Int- ligent computing is generally known to be computationally intensive from the point of view of resources required: time, memory, bandwidth. As such high resource c- sumption is one of its main drawbacks, distributed computing is expected to give an impetus to its practical utilization. Moreover, intelligent techniques have also proved their usefulness to the core distributed computing technologies like planning and scheduling, load balancing, replication, resource allocation and management, and its applications. Therefore, the emerging?eld of intelligent distributed computing can be expected both, to bring a fruitful cooperation and to pose new challenges of adaptation of both areas. Intelligent and Distributed Computing 2007 – IDC 2007 was the?rst Inter- tional Symposium aimed at bringing together researchers involved in intelligent and distributed computing to allow cross-fertilization and search for synergies of ideas and to enable advancement of research in these exciting sub-?elds of computer s- ence. IDC was started as an initiative of research groups from: (i) Systems Research Institute, Polish Academy of Sciences in Warsaw, Poland and (ii) Software Engine- ing Department of the University of Craiova, Craiova, Romania. IDC 2007 was held in Craiova, Romania during October 18-19, 2007. This book represents the peer-reviewed proceedings of the IDC 2007. We - ceived 52 submissions from 24 countries.

Intelligent computing covers a hybrid palette of methods and techniques - rived from classical arti?cial intelligence, computational intelligence, multi-agent systems a.o. Distributed computing studies systems that contain loosely-coupled components running on networked computers and that c- municateandcoordinatetheiractionsbyexchangeofmessages.Theemergent?eld of intelligent distributed computing is expected to pose special ch- lenges of adaptation and fruitful combination of results of both areas with a great impact on the development of new generation intelligent distributed information systems. Intelligent Distributed Computing – IDC Symposium Series was started as an initiative of research groups from: (i) Systems Research Institute, P- ish Academy of Sciences in Warsaw, Poland and (ii) Software Engineering Department of the University of Craiova, Craiova, Romania. IDC aims at bringing together researchers and practitioners involved in all aspects of - telligent distributed computing. IDC 2009 was the third event in this series and was hosted by Department of Computer Science, University of Cyprus in Ayia Napa, Cyprus during October 13-14, 2009.

This book represents the peer-reviewed proceedings of the Second International Symposium on Intelligent Distributed Computing – IDC 2008 held in Catania, Italy during September 18-19, 2008. The 35 contributions in this book address many topics related to intelligent and distributed computing, systems and applications, including: adaptivity and learning; agents and multi-agent systems; argumentation; auctions; case-based reasoning; collaborative systems; data structures; distributed algorithms; formal modeling and verification; genetic and immune algorithms; grid computing; information extraction, annotation and integration; network and security protocols; mobile and ubiquitous computing; ontologies and metadata; P2P computing; planning; recommender systems; rules; semantic Web; services and processes; trust and social computing; virtual organizations; wireless networks; XML technologies.

Knowledge-Driven Computing constitutes an emerging area of intensive research located at the intersection of Computational Intelligence and Knowledge Engineering with strong mathematical foundations. It embraces methods and approaches coming from diverse computational paradigms, such as evolutionary computation and nature-inspired algorithms, logic programming and constraint programming, rule-based systems, fuzzy sets and many others. The use of various knowledge representation formalisms and knowledge processing and computing paradigms is oriented towards the efficient resolution of computationally complex and difficult problems. The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches. More precisely, the ultimate goal has been to collect new knowledge representation, processing and computing paradigms which could be useful to practitioners involved in the area of discussion. To this end, contributions covering both theoretical aspects and practical solutions, and dealing with topics of interest for a wide audience, and/or cross-disciplinary research were preferred.

Clustering has been around for many decades and located itself in a uniquepositionasafundamentalconceptualandalgorithmiclandmark of data analysis. Almost since the very inception of fuzzy sets, the role and potential of these information granules in revealing and describing structureindatawasfullyacknowledgedandappreciated.Asamatter of fact, with the rapid growth of volumes of digital information, the role of clustering becomes even more visible and critical. Furthermore given the anticipated human centricity of the majority of artifacts of digitaleraandacontinuousbuildupofmountainsofdata,onebecomes fully cognizant of the growing role and an enormous potential of fuzzy sets and granular computing in the design of intelligent systems. In therecentyearsclusteringhasundergoneasubstantialmetamorphosis. Frombeinganexclusivelydata drivenpursuit,ithastransformeditself into a vehicle whose data centricity has been substantially augmented by the incorporation of domain knowledge thus giving rise to the next generation of knowledge-oriented and collaborative clustering. Interestingly enough, fuzzy clustering exhibits a dominant role in many developments of the technology of fuzzy sets including fuzzy modeling, fuzzy control, data mining, pattern recognition, and image processing. When browsing through numerous papers on fuzzy m- eling we can witness an important trend of a substantial reliance on fuzzy clustering being regarded as the general development tool. The same central position of fuzzy clustering becomes visible in pattern classi?ers and neurofuzzy systems. All in all, it becomes evident that further progress in fuzzy clustering is of vital relevance and bene?t to the overall progress of the area of fuzzy sets and their applications.

I think the next century will be the century of complexity. We have already discovered the basic laws that govern matter and understand all the normal situations. We don't know how the laws?t together, and what happens under extreme conditions. But I expect we will?nd a complete uni?ed theory sometime this century. There is no limit to the complexity that we can build using those basic laws. Stephen Hawking, January 2000. We don't know what we are talking about. Many of us believed that string theory was a very dramatic break with our previous notions of quantum theory. But now we learn that string theory, well, is not that much of a break. The state of physics today is like it was when we were mysti?ed by radioactivity. They were missing something absolutely fundamental. We are missing perhaps something as profound as they were back then. Nobel Laureate David Gross, December 2005. This volume is essentially a compilation of papers presented at the Int- national Workshop on Mathematics and Physics of Complex and Nonlinear Systems that was held at Indian Institute of Technology Kanpur, March 14 – 26, 2004 on the theme ChaNoXity: The Nonlinear Dynamics of Nature.

The first edition of the Encyclopedia of Complexity and Systems Science (ECSS, 2009) presented a comprehensive overview of granular computing (GrC) broadly divided into several categories: Granular computing from rough set theory, Granular Computing in Database Theory, Granular Computing in Social Networks, Granular Computing and Fuzzy Set Theory, Grid/Cloud Computing, as well as general issues in granular computing. In 2011, the formal theory of GrC was established, providing an adequate infrastructure to support revolutionary new approaches to computer/data science, including the challenges presented by so-called big data. For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily'things'are routinely granulated into sub'things': The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in data science.

Games, whether educational or recreational, are meant to be fun. How do we ensure that the game delivers its intent? The answer to this question is playtesting. However, a haphazard playtest process cannot discover play experience from various dimensions. Players'perceptions, affordances, age, gender, culture, and many more human factors influence play experience. A playtest requires an intensive experimental process and scientific protocols to ensure that the outcomes seen are reliable for the designer. Playtesting and players'affordances are the focus of this book. This book is not just about the playtest procedures but also demonstrates how they lead to the conclusions obtained when considering data sets. The playtest process or playtest stories differ according to the hypothesis under investigation. We cover examples of playtesting to identify the impact of human factors, such as age and gender, to examine a player's preferences for game objects'design and colors. The book details topics to reflect on possible emotional outcomes of the player at the early stages of game design as well as the methodology for presenting questions to players in such a way as to elicit authentic feedback. This book is intended mainly for game designers, researchers, and developers. However, it provides a general understanding of affordances and human factors that can be informative for readers working in any domain.

This book explores the interdisciplinary field of complex systems theory. By the end of the book, readers will be able to understand terminology that is used in complex systems and how they are related to one another; see the patterns of complex systems in practical examples; map current topics, in a variety of fields, to complexity theory; and be able to read more advanced literature in the field. The book begins with basic systems concepts and moves on to how these simple rules can lead to complex behavior. The author then introduces non-linear systems, followed by pattern formation, and networks and information flow in systems. Later chapters cover the thermodynamics of complex systems, dynamical patterns that arise in networks, and how game theory can serve as a framework for decision making. The text is interspersed with both philosophical and quantitative arguments, and each chapter ends with questions and prompts that help readers make more connections.“The text provides a useful overview of complex systems, with enough detail to allow a reader unfamiliar with the topic to understand the basics. The book stands out for its comprehensiveness and approachability. It will be particularly useful as a text for introductory physics courses. Tranquillo's strength is in delivering a vast amount of information in a succinct manner.… A reader can find information quickly and efficiently—that is, in my opinion, the book's greatest value.” (Stefani Crabtree, Physics Today)

Research on general video game playing aims at designing agents or content generators that can perform well in multiple video games, possibly without knowing the game in advance and with little to no specific domain knowledge. The general video game AI framework and competition propose a challenge in which researchers can test their favorite AI methods with a potentially infinite number of games created using the Video Game Description Language. The open-source framework has been used since 2014 for running a challenge. Competitors around the globe submit their best approaches that aim to generalize well across games. Additionally, the framework has been used in AI modules by many higher-education institutions as assignments, or as proposed projects for final year (undergraduate and Master's) students and Ph.D. candidates. The present book, written by the developers and organizers of the framework, presents the most interesting highlights of the research performed by the authors duringthese years in this domain. It showcases work on methods to play the games, generators of content, and video game optimization. It also outlines potential further work in an area that offers multiple research directions for the future.

(Preliminary) The book is a comprehensive collection of the most recent and significant research and applications in the field of fuzzy logic. It covers fuzzy structures, systems, rules, operations as well as important applications, e.g in decision making, environmental prediction and prevention, and communication. It is dedicated to Enric Trillas as an acknowledgement for his pioneering research in the field. The book include a foreword by Lotfi A. Zadeh.

Criticism is the habitus of the contemplative intellect, whereby we try to recognize with probability the genuine quality of a l- erary work by using appropriate aids and rules. In so doing, c- tain general and particular points must be considered. The art of interpretation or hermeneutics is the habitus of the contemplative intellect of probing into the sense of somewhat special text by using logical rules and suitable means. Note : Hermeneutics differs from criticism as the part does from the whole. Antonius Gvilielmus Amo Afer (1727) There is no such thing as absolute truth. At best it is a subj- tive criterion, but one based upon valuation. Unfortunately, too many people place their fate in the hands of subjective without properly evaluating it. Arnold A. Kaufmann and Madan M. Gupta The development of cost benefit analysis and the theory of fuzzy decision was divided into two inter-dependent structures of identification and measurement theory on one hand and fuzzy value theory one the other. Each of them has sub-theories that constitute a complete logical system.

Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu­ tionary search, into evolutionary algorithms has received increasing interest in the recent years. It has been shown from various motivations that knowl­ edge incorporation into evolutionary search is able to significantly improve search efficiency. However, results on knowledge incorporation in evolution­ ary computation have been scattered in a wide range of research areas and a systematic handling of this important topic in evolutionary computation still lacks. This edited book is a first attempt to put together the state-of-art and re­ cent advances on knowledge incorporation in evolutionary computation within a unified framework. Existing methods for knowledge incorporation are di­ vided into the following five categories according to the functionality of the incorporated knowledge in the evolutionary algorithms. 1. Knowledge incorporation in representation, population initialization, - combination and mutation. 2. Knowledge incorporation in selection and reproduction. 3. Knowledge incorporation in fitness evaluations. 4. Knowledge incorporation through life-time learning and human-computer interactions. 5. Incorporation of human preferences in multi-objective evolutionary com­ putation. The intended readers of this book are graduate students, researchers and practitioners in all fields of science and engineering who are interested in evolutionary computation. The book is divided into six parts. Part I contains one introductory chapter titled'A selected introduction to evolutionary computation'by Yao, which presents a concise but insightful introduction to evolutionary computation.

Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well as practical applications in engineering, science, business and commerce. The book covers central topics such as intelligent multi-agent systems, data mining, case-based reasoning, and rough sets. Essential techniques to the development of intelligent machines are investigated such as pattern recognition and classification, machine learning, natural language processing, grammar, evolutionary schemes, fuzzy-neural procedures, and intelligent vision. The book also includes useful applications ranging from medical diagnosis and technical/medical language translation, to power demand forecasting and manufacturing plants. Due to its depth and breadth of the coverage and the usefulness of the techniques and applications, this book is a valuable reference for experts and students alike.

This research book presents the agent theory and adaptation of agents in different contexts. Agents of different orders of complexity must be autonomous in the rules used. The agent must have a brain by which it can discover rules contained within the data. Because rules are the instruments by which agents change the environment, any adaptation of the rules can be considered as an evolution of the agents. Because uncertainty is present in every context, we shall describe in this book how it is possible to introduce global uncertainty from the local world into the description of the rules. This book contains ten chapters. Chapter 1 gives a general dscription of the evolutionary adaptation agent. Chapter 2 describes the actions and meta­ actions of the agent at different orders. Chapter 3 presents in an abstract and formal way the actions at different orders. Chapter 4 connects systems and meta systems with the adaptive agent. Chapter 5 describes the brain of the agent by the morphogenetic neuron theory. Chapter 6 introduces the logic structure of the adaptive agent. Chapter 7 describes the feedback and hyper-feedback in the adaptive agent. Chapter 8 introduces the adaptation field into the modal logic space as logic instrument in the adaptive agent. Chapter 9 describes the action of the agent in the physical domain. Chapter 10 presents the practical application of agents in robots and evolutionary computing.

Formal Languages and Applications provides a comprehensive study-aid and self-tutorial for graduates students and researchers. The main results and techniques are presented in an readily accessible manner and accompanied by many references and directions for further research. This carefully edited monograph is intended to be the gateway to formal language theory and its applications, so it is very useful as a review and reference source of information in formal language theory.

The book aims at surveying results in the application of fuzzy sets and fuzzy logic to economics and engineering. New results include fuzzy non-linear regression, fully fuzzified linear programming, fuzzy multi-period control, fuzzy network analysis, each using an evolutionary algorithm; fuzzy queuing decision analysis using possibility theory; fuzzy differential equations; fuzzy difference equations; fuzzy partial differential equations; fuzzy eigenvalues based on an evolutionary algorithm; fuzzy hierarchical analysis using an evolutionary algorithm; fuzzy integral equations. Other important topics covered are fuzzy input-output analysis; fuzzy mathematics of finance; fuzzy PERT (project evaluation and review technique). No previous knowledge of fuzzy sets is needed. The mathematical background is assumed to be elementary calculus.

The book is on the geometry of agent knowledge. The important concept studied in this book is the Field and its Geometric Representation. To develop a geometric image of the gravity, Einstein used Tensor Calculus but this is very different from the knowledge instruments used now, as for instance techniques of data mining, neural networks, formal concept analysis,quantum computer and other topics. The aim of this book is to rebuild the tensor calculus in order to give a geometric representation of agent knowledge. By using a new geometry of knowledge we can unify all the topics that have been studied in recent years to create a bridge between the geometric representation of the physical phenomena and the geometric representation of the individual and subjective knowledge of the agents.

Soft computing is playing an increasing role in the study of complex systems in science and engineering. There is a large spectrum of successful applications of soft computing in very different applications domains such as aerospace, communication, consumer appliances, electric power systems, process engineering, transportation, and manufacturing automation and robotics. It has taken a while to bring the early ideas of soft computing to an area and a discipline that seems to be more than appropriate for that. Here it is! This book studies SOFT computing in SOFTware engineering environment. The book is HARD in terms of its results. It covers a range of core topics from software engineering that are soft from its very nature: selection of components, software design, software reuse, software cost estimation and software processes. Soft computing differs from conventional (hard) computing in its ability to be tolerant of imprecision, uncertainty, partial truth, and approximation. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. The role model for soft computing is the human mind. This seems to be a natural fit with software engineering, a human-based development activity based on sound engineering principles. A recent survey by researchers reveals that'Software Engineering research tends to be quite self-contained, not relying on other disciplines for its thinking'.

Over the last few decades, research on handwriting recognition has made impressive progress. The research and development on handwritten word recognition are to a large degree motivated by many application areas, such as automated postal address and code reading, data acquisition in banks, text-voice conversion, security, etc. As the prices of scanners, com­ puters and handwriting-input devices are falling steadily, we have seen an increased demand for handwriting recognition systems and software pack­ ages. Some commercial handwriting recognition systems are now available in the market. Current commercial systems have an impressive performance in recognizing machine-printed characters and neatly written texts. For in­ stance, High-Tech Solutions in Israel has developed several products for container ID recognition, car license plate recognition and package label recognition. Xerox in the U. S. has developed TextBridge for converting hardcopy documents into electronic document files. In spite of the impressive progress, there is still a significant perfor­ mance gap between the human and the machine in recognizing off-line unconstrained handwritten characters and words. The difficulties encoun­ tered in recognizing unconstrained handwritings are mainly caused by huge variations in writing styles and the overlapping and the interconnection of neighboring characters. Furthermore, many applications demand very high recognition accuracy and reliability. For example, in the banking sector, although automated teller machines (ATMs) and networked banking sys­ tems are now widely available, many transactions are still carried out in the form of cheques.

The field called Learning Classifier Systems is populated with romantics. Why shouldn't it be possible for computer programs to adapt, learn, and develop while interacting with their environments? In particular, why not systems that, like organic populations, contain competing, perhaps cooperating, entities evolving together? John Holland was one of the earliest scientists with this vision, at a time when so-called artificial intelligence was in its infancy and mainly concerned with preprogrammed systems that didn't learn. that, like organisms, had sensors, took Instead, Holland envisaged systems actions, and had rich self-generated internal structure and processing. In so doing he foresaw and his work prefigured such present day domains as reinforcement learning and embedded agents that are now displacing the older'standard Af'. One focus was what Holland called'classifier systems': sets of competing rule­ like'classifiers', each a hypothesis as to how best to react to some aspect of the environment--or to another rule. The system embracing such a rule'popu­ lation'would explore its available actions and responses, rewarding and rating the active rules accordingly. Then'good'classifiers would be selected and re­ produced, mutated and even crossed, a la Darwin and genetics, steadily and reliably increasing the system's ability to cope.

Fuzzy logic provides a unique method of approximate reasoning in an imperfect world. This text is a bridge to the principles of fuzzy logic through an application-focused approach to selected topics in Engineering and Management. The many examples point to the richer solutions obtained through fuzzy logic and to the possibilities of much wider applications. There are relatively few texts available at present in fuzzy logic applications. The style and content of this text is complementary to those already available. New areas of application are presented in a graded approach in which the underlying concepts are first described. The text is broadly divided into two parts which treat Processes and Materials and also System Applications. The level enables a selection of the text to be made for the substance of a senior undergraduate level course. There is also sufficient volume and quality for the basis of a postgraduate course. A more restricted and judicious selection can provide the material for a professional short course.

Humanity's most basic intellectual quest to decipher nature and master it has led to numerous efforts to build machines that simulate the world or communi­ cate with it [Bus70, Tur36, MP43, Sha48, vN56, Sha41, Rub89, NK91, Nyc92]. The computational power and dynamic behavior of such machines is a central question for mathematicians, computer scientists, and occasionally, physicists. Our interest is in computers called artificial neural networks. In their most general framework, neural networks consist of assemblies of simple processors, or'neurons,'each of which computes a scalar activation function of its input. This activation function is nonlinear, and is typically a monotonic function with bounded range, much like neural responses to input stimuli. The scalar value produced by a neuron affects other neurons, which then calculate a new scalar value of their own. This describes the dynamical behavior of parallel updates. Some of the signals originate from outside the network and act as inputs to the system, while other signals are communicated back to the environment and are thus used to encode the end result of the computation.

This brief monograph is the first one to deal exclusively with the quantitative approximation by artificial neural networks to the identity-unit operator. Here we study with rates the approximation properties of the'right'sigmoidal and hyperbolic tangent artificial neural network positive linear operators. In particular we study the degree of approximation of these operators to the unit operator in the univariate and multivariate cases over bounded or unbounded domains. This is given via inequalities and with the use of modulus of continuity of the involved function or its higher order derivative. We examine the real and complex cases. For the convenience of the reader, the chapters of this book are written in a self-contained style.This treatise relies on author's last two years of related research work.Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The exposed results are expected to find applications in many areas of computer science and applied mathematics, such as neural networks, intelligent systems, complexity theory, learning theory, vision and approximation theory, etc. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science libraries.

The book provides strong evidence that research on the cognitive processes from arithmetic thought to algebraic thought should take into consideration the socio-cultural context. It is an important contribution to the literature on linguistic structure in comparative studies related to Chinese student mathematics learning. This book not only makes a great contribution to research in mathematics education, the findings of this study also addressed insightful approaches and thoughts of understanding the development of algebraic thinking in cultural contexts for classroom teachers. Using written Chinese language from different theoretical references provided wonderful approaches for understanding student algebra cognitive development in a different way and calls educators for to pay special attention to an epistemological and linguistic view of algebraic development. The findings inform classroom teachers that the cultural context plays an important role in student learning mathematics. A typical analysis of the cognitive dimension involved in some in the historical and cultural contexts is a great resource for classroom teachers. I really enjoyed reading this book and learned a lot from its compelling analysis. Shuhua An, Associate Professor and Director of Graduate Program in Mathematics Education, California State University, Long Beach

This volume presents a collection of recent studies covering the spectrum of computational intelligence applications with emphasis on their application to challenging real-world problems. Topics covered include: Intelligent agent-based algorithms, Hybrid intelligent systems, Cognitive and evolutionary robotics, Knowledge-Based Engineering, fuzzy sets and systems, Bioinformatics and Bioengineering, Computational finance and Computational economics, Data mining, Machine learning, and Expert systems.'Computational Intelligence in Optimization'is a comprehensive reference for researchers, practitioners and advanced-level students interested in both the theory and practice of using computational intelligence in real-world applications.

The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester?nal-year undergraduate, or?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the author's previous work on multi-sensor data [1] fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.

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.

Cet ouvrage traite des nouvelles fonctionnalités de MATLAB R2009, SIMULINK et STATEFLOW. Le premier chapitre permet la prise en main succincte de la plupart des fonctions MATLAB et SIMULINK. Tous les autres chapitres développent de façon approfondie les autres fonctionnalités du langage avec des applications du monde industriel (Régulation, Traitement de signal déterministe et aléatoire, Réseaux de neurones, etc.). L'ouvrage traite essentiellement MATLAB, SIMULINK et STATEFLOW, dont l'apprentissage se fait à travers des applications concrètes. Cet ouvrage s'adresse tant aux étudiants, scientifiques de l'industrie et des laboratoires de recherche ainsi qu'aux enseignants ainsi qu'aux chercheurs universitaires et industriels.

In conventional mathematical programming, coefficients of problems are usually determined by the experts as crisp values in terms of classical mathematical reasoning. But in reality, in an imprecise and uncertain environment, it will be utmost unrealistic to assume that the knowledge and representation of an expert can come in a precise way. The wider objective of the book is to study different real decision situations where problems are defined in inexact environment. Inexactness are mainly generated in two ways – (1) due to imprecise perception and knowledge of the human expert followed by vague representation of knowledge as a DM; (2) due to huge-ness and complexity of relations and data structure in the definition of the problem situation. We use interval numbers to specify inexact or imprecise or uncertain data. Consequently, the study of a decision problem requires answering the following initial questions: How should we compare and define preference ordering between two intervals?, interpret and deal inequality relations involving interval coefficients?, interpret and make way towards the goal of the decision problem? The present research work consists of two closely related fields: approaches towards defining a generalized preference ordering scheme for interval attributes and approaches to deal with some issues having application potential in many areas of decision making.

The Group Method of Data Handling (GMDH) is a typical inductive modeling method that is built on principles of self-organization for modeling complex systems. However, it is known to often under-perform on non-parametric regression tasks, while time series modeling GMDH exhibits a tendency to find very complex polynomials that cannot model well future, unseen oscillations of the series. In order to alleviate these problems, GMDH has been recently hybridized with some computational intelligence (CI) techniques resulting in more robust and flexible hybrid intelligent systems for solving complex, real-world problems. The central theme of this book is to present in a very clear manner hybrids of some computational intelligence techniques and GMDH approach. The hybrids discussed in the book include GP-GMDH (Genetic Programming-GMDH) algorithm, GA-GMDH (Genetic Algorithm-GMDH) algorithm, DE-GMDH (Differential Evolution-GMDH) algorithm, and PSO-GMDH (Particle Swarm Optimization) algorithm. Also included is the description of the recently introduced GAME (Group Adaptive Models Evolution algorithm. The hybrid character of models and their self-organizing ability give these hybrid self-organizing modeling systems an advantage over standard data mining models. The modeling and data mining solutions of several real-life problems in the areas of engineering, bioinformatics, finance, and economics are presented in the chapters. The book will benefit amongst others, people who are working in the areas of neural networks, machine learning, artificial intelligence, complex system modeling and analysis, and optimization.

The importance of tuning metaheuristics is widely acknowledged in scientific literature. However, there is very little dedicated research on the subject. Typically, scientists and practitioners tune metaheuristics by hand, guided only by their experience and by some rules of thumb. Tuning metaheuristics is often considered to be more of an art than a science. This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning. By adopting a machine learning perspective, the author gives a formal definition of the tuning problem, develops a generic algorithm for tuning metaheuristics, and defines an appropriate experimental methodology for assessing the performance of metaheuristics.

Evolvable Hardware (EHW) has emerged as a sub-domain of artificial evolution represented by a design methodology (consortium of methods) involving the application of Evolutionary Algorithms (EA) to the synthesis of digital and analogue electronic circuits and systems. Nevertheless, the most benefit for the society and indeed most revolutionizing application of EA is its hardware implementation leading to the EHW. These new EA based methodologies led to a new type of machines that is evolved to attain a desired behaviour, which means they have a behavioural computational intelligence. EHW is a special case of the adaptive hardware, namely being strongly related to the Adaptive Systems (AS) and the Adaptive Hardware (AH). The book presents a careful selection of the field that very well reflects the breadth of this high technology and its terminology and applications in context of the AS/AH. The harmonious symbiosis of the engineering approach and the accurate scientific methodology features the aspects of highly relevant and practical design principles governing the development of EHW and its connections with AS/AH. This book is both attractive and useful for everybody interested in the design and analysis of EHW in context of AS/AH and implementation of real time adaptive hardware hybrid intelligent systems.

Mathematics of Fuzziness – Basic Issues introduces a basic notion of ‘fuzziness'and provides a conceptual mathematical framework to characterize such fuzzy phenomena in Studies in Fuzziness and Soft Computing. The book systematically presents a self-contained introduction to the essentials of mathematics of fuzziness ranging from fuzzy sets, fuzzy relations, fuzzy numbers, fuzzy algebra, fuzzy measures, fuzzy integrals, and fuzzy topology to fuzzy control in a strictly mathematical manner. It contains most of the authors'research results in the field of fuzzy set theory and has evolved from the authors'lecture notes to both undergraduate and graduate students over the last three decades. A lot of exercises in each chapter of the book are particularly suitable as a textbook for any undergraduate and graduate student in mathematics, computer science and engineering. The reading of the book will surely lay a solid foundation for further research on fuzzy set theory and its applications.

It is well known that “fuzziness”—informationgranulesand fuzzy sets as one of its formal manifestations— is one of important characteristics of human cognitionandcomprehensionofreality. Fuzzy phenomena existinnature and are encountered quite vividly within human society. The notion of a fuzzy set has been introduced by L. A., Zadeh in 1965 in order to formalize human concepts, in connection with the representation of human natural language and computing with words. Fuzzy sets and fuzzy logic are used for mod- ing imprecise modes of reasoning that play a pivotal role in the remarkable human abilities to make rational decisions in an environment a?ected by - certainty and imprecision. A growing number of applications of fuzzy sets originated from the “empirical-semantic” approach. From this perspective, we were focused on some practical interpretations of fuzzy sets rather than being oriented towards investigations of the underlying mathematical str- tures of fuzzy sets themselves. For instance, in the context of control theory where fuzzy sets have played an interesting and practically relevant function, the practical facet of fuzzy sets has been stressed quite signi?cantly. However, fuzzy sets can be sought as an abstract concept with all formal underpinnings stemming from this more formal perspective. In the context of applications, it is worth underlying that membership functions do not convey the same meaning at the operational level when being cast in various contexts.

Dynamic environments abound, encompassing many real-world problems in fields as diverse as finance, engineering, biology and business. A vibrant research literature has emerged which takes inspiration from evolutionary processes to develop problem-solvers for these environments.'Foundations in Grammatical Evolution for Dynamic Environments'is a cutting edge volume illustrating current state of the art in applying grammar-based evolutionary computation to solve real-world problems in dynamic environments. The book provides a clear introduction to dynamic environments and the types of change that can occur. This is followed by a detailed description of evolutionary computation, concentrating on the powerful Grammatical Evolution methodology. It continues by addressing fundamental issues facing all Evolutionary Algorithms in dynamic problems, such as how to adapt and generate constants, how to enhance evolvability and maintain diversity. Finally, the developed methods are illustrated with application to the real-world dynamic problem of trading on financial time-series. The book was written to be accessible to a wide audience and should be of interest to practitioners, academics and students, who are seeking to apply grammar-based evolutionary algorithms to solve problems in dynamic environments.'Foundations in Grammatical Evolution for Dynamic Environments'is the second book dedicated to the topic of Grammatical Evolution.