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Intelligent Multimedia Multi-Agent Systems focuses on building intelligent successful systems. The book adopts a human-centered approach and considers various pragmatic issues and problems in areas like intelligent systems, software engineering, multimedia databases, electronic commerce, data mining, enterprise modeling and human-computer interaction for developing a human-centered virtual machine. The authors describe an ontology of the human-centered virtual machine which includes four components: activity-centered analysis component, problem solving adapter component, transformation agent component, and multimedia based interpretation component. These four components capture the external and internal planes of the system development spectrum. They integrate the physical, social and organizational reality on the external plane with stakeholder goals, tasks and incentives, and organization culture on the internal plane. The human-centered virtual machine and its four components are used for developing intelligent multimedia multi-agent systems in areas like medical decision support and health informatics, medical image retrieval, e-commerce, face detection and annotation, internet games and sales recruitment. The applications in these areas help to expound various aspects of the human-centered virtual machine including, human-centered domain modeling, distributed intelligence and communication, perceptual and cognitive task modeling, component based software development, and multimedia based data modeling. Further, the applications described in the book employ various intelligent technologies like neural networks, fuzzy logic and knowledge based systems, software engineering artifacts like agents and objects, internet technologies like XML and multimedia artifacts like image, audio, video and text.
This book will introduce students to intelligent agents, explain what these agents are, how they are constructed and how they can be made to co-operate effectively with one another in large-scale systems.
Learn how to employ JADE to build multi-agent systems! JADE (Java Agent DEvelopment framework) is a middleware for the development of applications, both in the mobile and fixed environment, based on the Peer-to-Peer intelligent autonomous agent approach. JADE enables developers to implement and deploy multi-agent systems, including agents running on wireless networks and limited-resource devices. Developing Multi-Agent Systems with JADE is a practical guide to using JADE. The text will give an introduction to agent technologies and the JADE Platform, before proceeding to give a comprehensive guide to programming with JADE. Basic features such as creating agents, agent tasks, agent communication, agent discovery and GUIs are covered, as well as more advanced features including ontologies and content languages, complex behaviours, interaction protocols, agent mobility, and the in-process interface. Issues such as JADE internals, running JADE agents on mobile devices, deploying a fault tolerant JADE platform, and main add-ons are also covered in depth. Developing Multi-Agent Systems with JADE: Comprehensive guide to using JADE to build multi-agent systems and agent orientated programming. Describes and explains ontologies and content language, interaction protocols and complex behaviour. Includes material on persistence, security and a semantics framework. Contains numerous examples, problems, and illustrations to enhance learning. Presents a case study demonstrating the use of JADE in practice. Offers an accompanying website with additional learning resources such as sample code, exercises and PPT-slides. This invaluable resource will provide multi-agent systems practitioners, programmers working in the software industry with an interest on multi-agent systems as well as final year undergraduate and postgraduate students in CS and advanced networking and telecoms courses with a comprehensive guide to using JADE to employ multi agent systems. With contributions from experts in JADE and multi agent technology.
Mark d'Inverno and Michael Luck present a formal approach to dealing with agents and agent systems in this second edition of Understanding Agent Systems. The Z specification language is used to establish an accessible and unified formal account of agent systems and inter-agent relationships. In particular, the framework provides precise and unambiguous meanings for common concepts and terms for agent systems, allows for the description of alternative agent models and architectures, and serves as a foundation for subsequent development of increasingly refined agent concepts. The practicability of this approach is verified by applying the formal framework to three detailed case studies. The book will appeal equally to researchers, students, and professionals in industry.
This is the first book treatment on two "hot button" topics in Information Systems, Computer Science and Education: the application of web technology for educational use. The result is a thorough and highly useful presentation on the confluence of the technical aspects of the Semantic Web and the field of Education or the art of teaching. The book will interest researchers and students in the fields of Information Systems, Computer Science, and Education.
Multiagent systems consist of multiple autonomous entities having different information and/or diverging interests. The study of multiagent systems (MAS) focuses on systems in which many intelligent agents interact with each other. The agents are considered to be autonomous entities, such as software programs or robots. Their interactions can be either cooperative or selfish. That is, the agents can share a common goal (e.g. an ant colony), or they can pursue their own interests. Multi-agent systems can be used to solve problems that are difficult or impossible for an individual agent or a monolithic system to solve. Intelligence may include some methodic, functional, procedural approach, algorithmic search or reinforcement learning. Although there is considerable overlap, a multi-agent system is not always the same as an agent-based model (ABM). The goal of an ABM is to search for explanatory insight into the collective behavior of obeying simple rules, typically in natural systems, rather than in solving specific practical or engineering problems. Topics where multi-agent systems research may deliver an appropriate approach include online trading, disaster response, and modelling social structures. Multi-agent systems consist of agents and their environment. Typically multi-agent systems research refers to software agents. However, the agents in a multi-agent system could equally well be robots, humans or human teams. A multi-agent system may contain combined humanagent teams. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains. This book, Multi-Agent Systems - Modeling, Control, Programming, Simulations and Applications, is intended to provide an emphasise on the multi-agent technology, products and industrial applications.
Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that comprises multiple intelligent agents interacting to solve problems that are beyond the capacities of individual agents. Modern Big Data Architectures examines modern concepts and architecture for Big Data processing and analytics. This unique, up-to-date volume provides joint analysis of big data and multi-agent systems, with emphasis on distributed, intelligent processing of very large data sets. Each chapter contains practical examples and detailed solutions suitable for a wide variety of applications. The author, an internationally-recognized expert in Big Data and distributed Artificial Intelligence, demonstrates how base concepts such as agent, actor, and micro-service have reached a point of convergence—enabling next generation systems to be built by incorporating the best aspects of the field. This book: Illustrates how data sets are produced and how they can be utilized in various areas of industry and science Explains how to apply common computational models and state-of-the-art architectures to process Big Data tasks Discusses current and emerging Big Data applications of Artificial Intelligence Modern Big Data Architectures: A Multi-Agent Systems Perspective is a timely and important resource for data science professionals and students involved in Big Data analytics, and machine and artificial learning.
Intelligent Multimedia Computing Science is an interdisciplinary field combining the arts, sciences, artificial intelligence, computer science, mathematics, and the humanities. The field presented is deeply rooted in Al, mathematical logic and models, modern communications, computer, and human sciences. Academic digital media studies are at times a partnership among Arts and Sciences, Computer Science, and Mathematics. The new fields encompass the intelligent and cognitive aspects of media arts and sciences, exploring the technical, cognitive, and aesthetic bases to human multimedia intelligence and its computation, the applications to business intelligence, model discovery, data mines and intelligent data bases, and IT. The monograph is a technical and practical book to the popular audience, to the business minded professionals, and to all groups wanting to be on an intelligent bearing to the new field.
2 chapter contains examples of intelligent agents, arranged according to their appli cation areas. Chapter 7 closes with a prospective view of the future development of intelligent agents. Everyone concerned with the Internet and the new possibilities of information and communication technology knows that nowadays there is no area that is devel oping faster. The authors are aware of the dynamics of this research area and its effects when they describe such a fast developing area in a slow, traditional me dium like a book. One thing is sure today: when the book appears on the market, new intelligent agents will already exist and some of the hypotheses made by this book will have been shown to be incorrect. Why, despite this, does it make sense to write a classical book on this subject? Is there an alternative? Experience shows that the majority of the people in business and public life who make decisions on the use of new technologies continue to prefer books and articles in periodicals rather than electronic sources such as the Internet. Or is there some other reason for the enormous success of Nicolas Negroponte's book Being Digital, which we thank for multimedia and many concepts of the digital and networked world, and even intelligent agents? Today, a book is still the only way to establish a new area.
This review volume introduces the novel intelligent Web theory calledcomputational Web intelligence (CWI) based on computationalintelligence (CI) and Web technology (WT). It takes an in-depth lookat hybrid Web intelligence (HWI), which is based on artificialbiological and computational intelligence with Web technology and isused to build hybrid intelligent Web systems that serve wired andwireless users more efficiently.