An Introduction to MultiAgent Systems

An Introduction to MultiAgent Systems

Author: Michael Wooldridge

Publisher: John Wiley & Sons

Published: 2009-06-22

Total Pages: 484

ISBN-13: 0470519460

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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


An Introduction to MultiAgent Systems

An Introduction to MultiAgent Systems

Author: Michael Wooldridge

Publisher: John Wiley & Sons

Published: 2002-05-13

Total Pages: 386

ISBN-13:

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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.


Multi-agent Systems

Multi-agent Systems

Author: Jacques Ferber

Publisher: Addison-Wesley Professional

Published: 1999

Total Pages: 536

ISBN-13:

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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.


Distributed Coordination of Multi-agent Networks

Distributed Coordination of Multi-agent Networks

Author: Wei Ren

Publisher: Springer Science & Business Media

Published: 2010-11-30

Total Pages: 312

ISBN-13: 0857291696

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Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.


Beyond Artificial Intelligence

Beyond Artificial Intelligence

Author: Jozef Kelemen

Publisher: Springer Science & Business Media

Published: 2012-10-20

Total Pages: 243

ISBN-13: 3642344216

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Products of modern artificial intelligence (AI) have mostly been formed by the views, opinions and goals of the “insiders”, i.e. people usually with engineering background who are driven by the force that can be metaphorically described as the pursuit of the craft of Hephaestus. However, since the present-day technology allows for tighter and tighter mergence of the “natural” everyday human life with machines of immense complexity, the responsible reaction of the scientific community should be based on cautious reflection of what really lies beyond AI, i.e. on the frontiers where the tumultuous ever-growing and ever-changing cloud of AI touches the rest of the world. The chapters of this boo are based on the selected subset of the presentations that were delivered by their respective authors at the conference “Beyond AI: Interdisciplinary Aspects of Artificial Intelligence” held in Pilsen in December 2011. From its very definition, the reflection of the phenomena that lie beyond AI must be inherently interdisciplinary. And so is this book: all the authors took part in a mutual transdisciplinary dialogue after explaining their views on AI not only to a narrow selection of their usual close peers with the same specialisation, but to a much broader audience of various experts from AI engineering, natural sciences, humanities and philosophy. The chapters of this book thus reflect results of such a dialogue.


Multi-Objective Decision Making

Multi-Objective Decision Making

Author: Diederik M. Zhou

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 111

ISBN-13: 3031015762

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Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.


Issues in Multi-Agent Systems

Issues in Multi-Agent Systems

Author: Antonio Moreno

Publisher: Springer Science & Business Media

Published: 2007-12-22

Total Pages: 229

ISBN-13: 376438543X

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Discover the latest developments and issues in multi-agent systems by exploring their applications in various domains such as electronic markets, e-tourism, ambience intelligence, and complex system analysis. The book is written by two researchers with hands-on experience in technology transfer. With their practical focus, they help you see how agent technology can be applied in many new services and environments.


Control of Multi-agent Systems

Control of Multi-agent Systems

Author: Masaaki Nagahara

Publisher: Springer

Published: 2024-05-09

Total Pages: 0

ISBN-13: 9783031529801

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This textbook teaches control theory for multi-agent systems. Readers will learn the basics of linear algebra and graph theory, which are then developed to describe and solve multi-agent control problems. The authors address important and fundamental problems including: • consensus control; • coverage control; • formation control; • distributed optimization; and • the viral spreading phenomenon. Students' understanding of the core theory for multi-agent control is enhanced through worked examples and programs in the popular Python language. End-of-chapter exercises are provided to help assess learning progress. Instructors who adopt the book for their courses can download a solutions manual and the figures in the book for lecture slides. Additionally, the Python programs are available for download and can be used for experiments by students in advanced undergraduate or graduate courses based on this text. The broad spectrum of applications relevant to this material includes the Internet of Things, cyber-physical systems, robot swarms, communications networks, smart grids, and truck platooning. Additionally, in the spheres of social science and public health, it applies to opinion dynamics and the spreading of viruses in social networks. Students interested in learning about such applications, or in pursuing further research in multi-agent systems from a theoretical perspective, will find much to gain from Control of Multi-agent Systems. Instructors wishing to teach the subject will also find it beneficial.


Autonomous Agents and Multi-agent Systems

Autonomous Agents and Multi-agent Systems

Author: Jiming Liu

Publisher: World Scientific

Published: 2001

Total Pages: 302

ISBN-13: 9810242824

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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.


Conflicting Agents

Conflicting Agents

Author: Cathérine Tessier

Publisher: Springer Science & Business Media

Published: 2005-12-27

Total Pages: 342

ISBN-13: 0306469855

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Conflicts between agents acting in a multi-agent environment arise for different reasons, involve different concepts, and are dealt with in different ways, depending on the kind of agents and on the domain where they are considered. Agents may have conflicting beliefs, conflicting goals, or may have to share limited resources. Consequently, conflicts may be expressed as mere differences, or as contradictions, or even as social conflicts. They may be avoided, solved, kept, or even created deliberately. Conflicting Agents studies conflicts in the context of multi-agent systems, i.e. artificial societies modeled on the basis of autonomous, interacting agents. This book addresses questions about types of conflicts, conflict definitions and the use of conflicts as trigger functions for activities in multi-agent systems. The book is also dedicated to questions of conflict management, resolution and avoidance, i.e. the question of how agents cope with conflicts and conflicting situations.