Agent And Multi Agent Systems

The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems The main application areas of agent-based systems

The main concepts and techniques of multi-agent oriented programming, which supports the multi-agent systems paradigm at the programming level. A multi-agent system is an organized ensemble of autonomous, intelligent, goal-oriented entities called agents, communicating with each other and interacting within an environment. This book introduces the main concepts and techniques of multi-agent oriented programming, (MAOP) which supports the multi-agent systems paradigm at the programming level. MAOP provides a structured approach based on three integrated dimensions, which the book examines in detail: the agent dimension, used to design the individual (interacting) entities; the environment dimension, which allows the development of shared resources and connections to the real world; and the organization dimension, which structures the interactions among the autonomous agents and the shared environment.

Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science. This book surveys the state of the art in this emerging field by drawing together thoroughly selected reviewed papers from two related workshops; as well as papers by leading researchers specifically solicited for this book. The articles are organized into topical sections on - learning, cooperation, and communication - emergence and evolution in multi-agent systems - theoretical foundations of adaptive agents

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.

Agent systems are being used to model complex systems like societies, markets and biological systems. In this book we investigate issues of agent systems related to convergence and interactivity using techniques from agent based modelling to simulate complex systems, and demonstrate that interactivity/exchange and convergence in multi-agent systems are issues that are significantly interrelated. Topic and features: - Introduces the state of the art in multi-agent systems, with an emphasis on agent-based computational economics. - Sheds light on the fundamental concepts behind the stability of multi-agent systems. - Investigates knowledge exchange among agents, the rationale behind it and its effects on the ecosystem. - Explores how information provided through interaction with the system can be used to optimise its performance. - Describes a pricing strategy for a realistic large-scale distributed system. This book supplies a comprehensive resource and will be invaluable reading for researchers and postgraduates studying this topic.

Methodological Guidelines for Modeling and Developing MAS-Based Simulations The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field’s history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications. Simulation for MAS — explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction. MAS for Simulation — discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools — presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue. Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.

In this book, Jacques Ferber has brought together all the recent developments in the field of multi-agent systems - an area that has seen increasing interest and major developments over the last few years. The author draws on work carried out in various disciplines, including information technology, sociology and cognitive psychology to provide a coherent and instructive picture of the current state-of-the-art. The book introduces and defines the fundamental concepts that need to be understood, clearly describes the work that has been done, and invites readers to reflect upon the possibilities of the future.

Multi-agent systems are claimed to be especially suited to the development of software systems that are decentralized, can deal flexibly with dynamic conditions, and are open to system components that come and go. This is why they are used in domains such as manufacturing control, automated vehicles, and e-commerce markets. Danny Weyns' book is organized according to the postulate that "developing multi-agent systems is 95% software engineering and 5% multi-agent systems theory." He presents a software engineering approach for multi-agent systems that is heavily based on software architecture - with, for example, tailored patterns such as "situated agent", "virtual environment", and "selective perception" - and on middleware for distributed coordination – with programming abstractions such as "views" and "roles." Next he shows the feasibility and applicability of this approach with the development of an automated transportation system consisting of a number of automatic guided vehicles transporting loads in an industrial setting. Weyns puts the development of multi-agent systems into a larger perspective with traditional software engineering approaches. With this, he opens up opportunities to exploit the body of knowledge developed in the multi-agent systems community to tackle some of the difficult challenges of modern-day software systems, such as decentralized control, location-awareness, self-adaption, and large-scale. Thus his book is of interest for both researchers and industrial software engineers who develop applications in areas such as distributed control systems and mobile applications where such requirements are of crucial importance.