Opportunities And Challenges For Next Generation Applied Intelligence

The term “Artificial Intelligence” has been used since 1956 and has become a very popular research field. Generally, it is the study of the computations that enable a system to perceive, reason and act. In the early days, it was expected to achieve the same intelligent behavior as a human, but found impossible at last. Its goal was thus revised to design and use of intelligent methods to make systems more ef- cient at solving problems. The term “Applied Intelligence” was thus created to represent its practicality. It emphasizes applications of applied intelligent systems to solve real-life problems in all areas including engineering, science, industry, automation, robotics, business, finance, medicine, bio-medicine, bio-informatics, cyberspace, and man-machine interactions. To endow the intelligent behavior of a system, many useful and interesting techniques have been developed. Some of them are even borrowed from the na- ral observation and biological phenomenon. Neural networks and evolutionary computation are two examples of them. Besides, some other heuristic approaches like data mining, adaptive control, intelligent manufacturing, autonomous agents, bio-informatics, reasoning, computer vision, decision support systems, expert s- tems, fuzzy logic, robots, intelligent interfaces, internet technology, planning and scheduling, are also commonly used in applied intelligence.

The International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE), always sponsored by the International So- ety of Applied Intelligence (ISAI), emphasizes applications of applied intelligent systems to solve real-life problems in all areas. It is held every year and has become one of the biggest and most important academic activities concerning the theory and applications of intelligent systems in the world. The IEA/AIE 2009 conference was hosted by the National University of Tainan and National University of Kaohsiung in Taiwan. This was the first time that the IEA/AIE conference was held in Taiwan. We received 286 papers from all parts of the world. Only 84 papers were selected for publication in this volume of LNAI proceedings. Each paper was reviewed by at least two anonymous referees to assure the high quality. We would like to express our sincere thanks to the Program Committee members and all the reviewers for their hard work, which helped us to select the highest quality papers for the conference. These papers highlight opportunities and challenges for the next generation of applied int- ligence and reveal technological innovations in real applications.

The presentations of theinvitedspeakersandauthorsmainlyfocusedondevelopingandstudyingnew methods to cope with the problems posed by real-life applications of arti?cial intelligence.Paperspresentedinthetwentythirdconferenceintheseriescovered theories as well as applications of intelligent systems in solving complex real-life problems. We received 297 papers for the main track, selecting 119 of them with the highest quality standards. Each paper was revised by at least three members of the Program Committee.

Emotional Intelligence is a new discipline of knowledge, dealing with modeling, recognition and control of human emotions. The book Emotional Intelligence: A Cybernetic Approach, to the best of the authors’ knowledge is a first compreh- sive text of its kind that provides a clear introduction to the subject in a precise and insightful writing style. It begins with a philosophical introduction to E- tional Intelligence, and gradually explores the mathematical models for emotional dynamics to study the artificial control of emotion using music and videos, and also to determine the interactions between emotion and logic from the points of view of reasoning. The later part of the book covers the chaotic behavior of - existing emotions under certain conditions of emotional dynamics. Finally, the book attempts to cluster emotions using electroencephalogram signals, and d- onstrates the scope of application of emotional intelligence in several engineering systems, such as human-machine interfaces, psychotherapy, user assistance s- tems, and many others. The book includes ten chapters. Chapter 1 provides an introduction to the s- ject from a philosophical and psychological standpoint. It outlines the fundamental causes of emotion arousal, and typical characteristics of the phenomenon of an emotive experience. The relation between emotion and rationality of thoughts is also introduced here. Principles of natural regulation of emotions are discussed in brief, and the biological basis of emotion arousal using an affective neu- scientific model is introduced next.

Computational Intelligence (CI) and Bioprocess are well-established research areas which have much to offer each other. Under the perspective of the CI area, Biop- cess can be considered a vast application area with a growing number of complex and challenging tasks to be dealt with, whose solutions can contribute to boosting the development of new intelligent techniques as well as to help the refinement and s- cialization of many of the already existing techniques. Under the perspective of the Bioprocess area, CI can be considered a useful repertoire of theories, methods and techniques that can contribute and offer interesting alternative approaches for solving many of its problems, particularly those hard to solve using conventional techniques. Although throughout the past years CI and Bioprocess areas have accumulated substantial specific knowledge and progress has been quick and with a high degree of success, we believe there is still a long way to go in order to use the potentialities of the available CI techniques and knowledge at their full extent, as tools for supporting problem solving in bioprocesses. One of the reasons is the fact that both areas have progressed steadily and have been continuously accumulating and refining specific knowledge; another reason is the high level of technical expertise demanded by each of them. The acquisition of technical skills, experience and good insights in either of the two areas is very demanding and a hard task to be accomplished by any professional.

Intelligent systems and technologies are increasing finding their ways in our daily lives. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems; A Fuzzy Density Analysis of Subgroups by means of DNA Oligonucleotides; Evolution of Cooperating Classification Rules with an Archiving Strategy to Underpin Collaboration; Designing Agents with Dynamic Capability; Localized versus Locality Preserving Representation Methods in Face Recognition Tasks; Invariance Properties of Recurrent Neural Networks; Solving Bioinformatics Problems by Soft Computing Techniques; Transforming an Interactive Expert Code into a Statefull Service and a Multicoreenabled System; Ro-WordNet with Paradigmatic Morphology and Subjectivity Mark-up; Special Cases of Relative Object Qualification using the AMONG Operator; Effective Speaker Tracking Strategies for Multi-party Human-Computer Dialogue; The Fuzzy Interpolative Control for Passive Greenhouses; GPS safety system for airplanes; 3D Collaborative Interfaces for E-learning; Open Projects in Contemporary E-Learning; Software Platform for Archaeological Patrimony Inventory and Management. The book is directed to the graduate students, researchers, professors and the practitioner of intelligent systems.

This book explores the increasing convergence of Social Media and Semantic Web technologies. It offers up-to-date contributions that illustrate various approaches to this young and emerging technology area.

During the last two decades, the idea of Semantic Web has received a great deal of attention. An extensive body of knowledge has emerged to describe technologies that seek to help us create and use aspects of the Semantic Web. Ontology and agent-based technologies are understood to be the two important technologies here. A large number of articles and a number of books exist to describe the use individually of the two technologies and the design of systems that use each of these technologies individually, but little focus has been given on how one can - sign systems that carryout integrated use of the two different technologies. In this book we describe ontology and agent-based systems individually, and highlight advantages of integration of the two different and complementary te- nologies. We also present a methodology that will guide us in the design of the - tegrated ontology-based multi-agent systems and illustrate this methodology on two use cases from the health and software engineering domain. This book is organized as follows: • Chapter I, Current issues and the need for ontologies and agents, describes existing problems associated with uncontrollable information overload and explains how ontologies and agent-based systems can help address these - sues. • Chapter II, Introduction to multi-agent systems, defines agents and their main characteristics and features including mobility, communications and collaboration between different agents. It also presents different types of agents on the basis of classifications done by different authors.