Knowledge processing and decision making in agent-based systems constitute the key components of intelligent machines. The contributions included in the book are: Innovations in Knowledge Processing and Decision Making in Agent-Based Systems Towards Real-World HTN Planning Agents Mobile Agent-Based System for Distributed Software Maintenance Software Agents in New Generation Networks: Towards the Automation of Telecom Processes Multi-agent Systems and Paraconsistent Knowledge An Agent-based Negotiation Platform for Collaborative Decision-Making in Construction Supply Chain An Event-Driven Algorithm for Agents at the Web A Generic Mobile Agent Framework Toward Ambient Intelligence Developing Actionable Trading Strategies Agent Uncertainty Model and Quantum Mechanics Representation Agent Transportation Layer Adaptation System Software Agents to Enable Service Composition through Negotiation Advanced Technology Towards Developing Decentralized Autonomous Flexible Manufacturing Systems

Intelligent paradigms are increasingly finding their ways in the design and development of decision support systems. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems in decision making - A new method of ranking intuitionistic fuzzy alternatives - Fuzzy rule base model identification by bacterial memetic algorithms - Discovering associations with uncertainty from large databases - Dempster-Shafer structures, monotonic set measures and decision making - Interpretable decision-making models - A general methodology for managerial decision making - Supporting decision making via verbalization of data analysis results using linguistic data summaries - Computational intelligence in medical decisions making. This book is directed to the researchers, graduate students, professors, decision makers and to those who are interested to investigate intelligent paradigms in decision making.

The book consists of 31 chapters in which the authors deal with multiple aspects of modeling, utilization and implementation of semantic methods for knowledge management and communication in the context of human centered computing. It is assumed that the modern human centered computing requires the intensive application of these methods as well as effective integration with multiple techniques of computational collective intelligence. The book is organized in four parts devoted to the presentation of utilization of knowledge processing in agent and multiagent systems, application of computational collective intelligence to knowledge management, models for collectives of intelligent agents, and models and environments tailored directly to human-centered computing. All chapters in the book discuss theoretical and practical issues related to various models and aspects of computational techniques for semantic methods, which are currently studied and developed in many academic and industry centers over the world. The editors hope that the book can be useful for graduate and PhD students of computer science, as well as for mature academics, researchers and practitioners interested in developing of modern methods for representation, processing and distribution of knowledge in the context of human centered computing and by means of computer based information systems. It is the hope of the editors that readers of this volume can find in all chosen chapters many inspiring ideas and influential practical examples, as well as use them in their current and future work.

This book presents some of the latest applications of new theories based on the concept of paraconsistency and correlated topics in informatics, such as pattern recognition (bioinformatics), robotics, decision-making themes, and sample size. Each chapter is self-contained, and an introductory chapter covering the logic theoretical basis is also included. The aim of the text is twofold: to serve as an introductory text on the theories and applications of new logic, and as a textbook for undergraduate or graduate-level courses in AI. Today AI frequently has to cope with problems of vagueness, incomplete and conflicting (inconsistent) information. One of the most notable formal theories for addressing them is paraconsistent (paracomplete and non-alethic) logic.

This book constitutes the proceedings of the 4th KES International Symposium on Agent and Multi-Agent Systems, KES-AMSTA 2010, held in June 2010 in Gdynia, Poland. The discussed field is concerned with the development and analysis of AI-based problem-solving and control architectures for both single-agent and multiple-agent systems. Only 83 papers were selected for publication in both volumes and focus on topics such as: Multi-Agent Systems Design and Implementation, Negotiations and Social Issues, Web Services and Semantic Web, Cooperation, Coordination and Teamwork, Agent-Based Modeling, Simulation and Decision Making, Multi-Agent Applications, Management and e-Business, Mobile Agents and Robots, and Machine Learning.

This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.

This book provides an overview of multi-agent systems and several applications that have been developed for real-world problems. Multi-agent systems is an area of distributed artificial intelligence that emphasizes the joint behaviors of agents with some degree of autonomy and the complexities arising from their interactions. Multi-agent systems allow the subproblems of a constraint satisfaction problem to be subcontracted to different problem solving agents with their own interest and goals. This increases the speed, creates parallelism and reduces the risk of system collapse on a single point of failure. Different multi-agent architectures, that are tailor-made for a specific application are possible. They are able to synergistically combine the various computational intelligent techniques for attaining a superior performance. This gives an opportunity for bringing the advantages of various techniques into a single framework. It also provides the freedom to model the behavior of the system to be as competitive or coordinating, each having its own advantages and disadvantages.

The SAGE Encyclopedia of Educational Technology examines information on leveraging the power of technology to support teaching and learning. While using innovative technology to educate individuals is certainly not a new topic, how it is approached, adapted, and used toward the services of achieving real gains in student performance is extremely pertinent. This two-volume encyclopedia explores such issues, focusing on core topics and issues that will retain relevance in the face of perpetually evolving devices, services, and specific techniques. As technology evolves and becomes even more low-cost, easy-to-use, and more accessible, the education sector will evolve alongside it. For instance, issues surrounding reasoning behind how one study has shown students retain information better in traditional print formats are a topic explored within the pages of this new encyclopedia. Features: A collection of 300-350 entries are organized in A-to-Z fashion in 2 volumes available in a choice of print or electronic formats. Entries, authored by key figures in the field, conclude with cross references and further readings. A detailed index, the Reader’s Guide themes, and cross references combine for search-and-browse in the electronic version. This reference encyclopedia is a reliable and precise source on educational technology and a must-have reference for all academic libraries.

Computational collective intelligence (CCI) is most often understood as a subfield of artificial intelligence (AI) dealing with soft computing methods that enable group decisions to be made or knowledge to be processed among autonomous units acting in distributed environments. The needs for CCI techniques and tools have grown signi- cantly recently as many information systems work in distributed environments and use distributed resources. Web-based systems, social networks and multi-agent systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. Therefore, CCI is of great importance for today’s and future distributed systems. Methodological, theoretical and practical aspects of computational collective int- ligence, such as group decision making, collective action coordination, and knowledge integration, are considered as the form of intelligence that emerges from the collabo- tion and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc. , can support human and other collective intelligence and create new forms of CCI in natural and/or artificial s- tems.

"This research book is a repository for academicians, researchers, and industry practitioners to share and exchange their research ideas, theories, and practical experiences, discuss challenges and opportunities, and present tools and techniques in all aspects of e-business development and management in the digital economy"--Provided by publisher.