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 paradigm of self-organisation is fundamental to theories of collective action in economic science and democratic governance in political science. Self-organisation in these social systems critically depends on voluntary compliance with conventional rules: that is, rules which are made up, mutually agreed, and modifiable 'on the fly'. How, then, can we use the self-organisation observed in such social systems as an inspiration for decentralised computer systems, which can face similar problems of coordination, cooperation and collaboration between autonomous peers?Self-Organising Multi-Agent Systems presents an innovative and systematic approach to transforming theories of economics and politics (and elements of philosophy, psychology, and jurisprudence) into an executable logical specification of conventional rules. It shows how sets of such rules, called institutions, provide an algorithmic basis for designing and implementing cyber-physical systems, enabling intelligent software processes (called agents) to manage themselves in the face of competition for scarce resources. It also provides a basis for implementing socio-technical systems with interacting human and computational intelligences in a way that is sustainable, fair and legitimate.This interdisciplinary book is essential reading for anyone interested in the 'planned emergence' of global properties, commonly-shared values or successful collective action, especially as a product of social construction, knowledge management and political arrangements. For those studying both computer science and social sciences, this book offers a radically new gateway to a transformative understanding of complex system development and social system modelling.Understanding how a computational representation of qualitative values like justice and democracy can lead to stability and legitimacy of socio-technical systems is among the most pressing software engineering challenges of modern times. This book can be read as an invitation to make the Digital Society better.Related Link(s)

Fifteen papers were presented at the first workshop on Multi-Agent Systems and Agent-Based Simulation held as part of the Agents World conference in Paris, July 4-- 6, 1998. The workshop was designed to bring together two developing communities: the multi-agent systems researchers who were the core participants at Agents World, and social scientists interested in using MAS as a research tool. Most of the social sciences were represented, with contributions touching on sociology, management science, economics, psychology, environmental science, ecology, and linguistics. The workshop was organised in association with SimSoc, an informal group of social scientists who have arranged an irregular series of influential workshops on using simulation in the social sciences beginning in 1992. While the papers were quite heterogeneous in substantive domain and in their disciplinary origins, there were several themes which recurred during the workshop. One of these was considered in more depth in a round table discussion led by Jim Doran at the end of the workshop on 'Representing cognition for social simulation', which addressed the issue of whether and how cognition should be modelled. Quite divergent views were expressed, with some participants denying that individual cognition needed to be modelled at all, and others arguing that cognition must be at the centre of social simulation.

The relatively new scientific field of economic agent-based systems is a promising, but yet not completely developed area of economics, at the frontier to business administration, computer sciences, and the social sciences. This book follows a rather interdisciplinary approach while maintaining a focus on the economic dimension of agent-based models. In contrast to other literature in this field, this book aims at developing a framework for modelling an economic system in the sense of a total model of the economy. The design and implementation of the agent-based framework AS1 are described in detail. Some sample applications, such as an analysis of the effects of the presence of different research institutes providing alternative inconsistent forecasts for the private agents, provide an overview of the strengths of an agent-based economic model. This 2nd edition is a reprint of the original Edition (from 2006).

"This book delivers definitive research on the use of agent technologies to advance the practice of electronic business in today's organizations, targeting the needs of enterprises in open and dynamic business opportunities to incorporate skilled use of multiple independent information systems. It clearly articulates the stages involved in developing agent-based e-business systems"--Provided by publisher.

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.

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.

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

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.

An autonomous agent is a computational system that acquires sensory data from its environment and decides by itself how to relate the external stimulus to its behaviors in order to attain certain goals. Responding to different stimuli received from its task environment, the agent may select and exhibit different behavioral patterns. The behavioral patterns may be carefully predefined or dynamically acquired by the agent based on some learning and adaptation mechanism(s). In order to achieve structural flexibility, reliability through redundancy, adaptability, and reconfigurability in real-world tasks, some researchers have started to address the issue of multiagent cooperation. Broadly speaking, the power of autonomous agents lies in their ability to deal with unpredictable, dynamically changing environments. Agent-based systems are becoming one of the most important computer technologies, holding out many promises for solving real-world problems. The aims of this book are to provide a guided tour to the pioneering work and the major technical issues in agent research, and to give an in-depth discussion on the computational mechanisms for behavioral engineering in autonomous agents. Through a systematic examination, the book attempts to provide the general design principles for building autonomous agents and the analytical tools for modeling the emerged behavioral properties of a multiagent system.