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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
Multiagent systems (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value. It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.
Agents in multiagent systems are concurrent autonomous entities that need to coordinate and to cooperate so as to perform their tasks; these coordination and cooperation tasks might be achieved through communication. Communication, also called interaction by some authors, thus represents one of the major topics in multiagent systems. The state of the art of research on communication in multiagent systems is presented in this book. First, three seminal papers by Cohen and Perrault, by Singh, and by Davis and Smith present background information and introduce the newcomer to the area. The main part of the book is devoted to current research work dealing with agent communication, communication for coordination and argumentation, protocols, and dialogue games and conversational agents. Finally, the last paper deals with the future of agent communication.
In this book, we present a collection of papers around the topic of agent com- nication. The communication between agents has been one of the major topics of research in multiagent systems. The current work can therefore build on a number of previous Workshops of which the proceedings have been published in earlier volumes in this series. The basis of this collection is formed by the accepted submissions of the Workshop on Agent Communication held in c- junction with the AAMAS Conference in July 2004 in New York. The workshop received 26 submissions of which 14 were selected for publication in this v- ume. Besides the high-quality workshop papers we noticed that many papers on agent communication found their way to the main conference. We decided therefore to invite a number of authors to revise and extend their papers from this conference and to combine them with the workshop papers. We believe that the current collection comprises a very good and quite complete overview of the state of the art in this area of research and gives a good indication of the topics that are of major interest at the moment. The papers can roughly be divided over the following ?ve themes: – social commitments – multiparty communication – content languages – dialogues and conversations – speech acts Although these themes are of course not mutually exclusive they indicate some main directions of research. We therefore have arranged the papers in the book according to the topics indicated above.
Cooperative Control of Multi-Agent Systems extends optimal control and adaptive control design methods to multi-agent systems on communication graphs. It develops Riccati design techniques for general linear dynamics for cooperative state feedback design, cooperative observer design, and cooperative dynamic output feedback design. Both continuous-time and discrete-time dynamical multi-agent systems are treated. Optimal cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely treated in literature are developed. Results spanning systems with first-, second- and on up to general high-order nonlinear dynamics are presented. Each control methodology proposed is developed by rigorous proofs. All algorithms are justified by simulation examples. The text is self-contained and will serve as an excellent comprehensive source of information for researchers and graduate students working with multi-agent systems.
A first attempt to develop a standardized agent communication language (ACL) resulted in KQML, probably the most widely used such language. However, a lot of technical work remains to be done. Even worse, so far, there seems to be little consensus on the basics of agent communication and there is no clear understanding of the semantics of individual speech acts or even of the basic concepts that should be used to define the semantics. This book documents two workshops on communication in MAS held in 1999, one on Specifying and Implementing Conversation Policies (SICP) and the other in Agent Communication Languages and presents the current state of the art of research in the field. A detailed introductory overview by the volume editors highlights a number of issues that play an important role in agent communication.
Agent technology has recently become one of the most vibrant and fastest growing areas in information technology. This is the first systematic introduction to software agents with the goal of exploiting them in future communication systems. The coherently written chapters provide complementary coverage of the relevant issues. Multi-agent systems and mobile agent approaches are presented and applied to important topics in future communication 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
Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.
This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence that is suitable as a textbook.