Objective Coordination in Multi-Agent System Engineering
Objective Coordination in Multi-Agent System Engineering

Author: Michael Schumacher

Publisher: Springer

Published: 2003-06-29

Total Pages: 150

ISBN-13: 3540449337

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Based on a suitably defined coordination model distinguishing between objective (inter-agent) coordination and subjective (intra-agent) coordination, this book addresses the engineering of multi-agent systems and thus contributes to closing the gap between research and applications in agent technology. After reviewing the state of the art, the author introduces the general coordination model ECM and the corresponding object-oriented coordination language STL++. The practicability of ECM/STL++ is illustrated by the simulation of a particular collective robotics application and the automation of an e-commerce trading system. Situated at the intersection of behavior-based artificial intelligence and concurrent and distributed systems, this monograph is of relevance to the agent R&D community approaching agent technology from the distributed artificial intelligence point of view as well as for the distributed systems community.

Intelligent Information Agents
Intelligent Information Agents

Author: Matthias Klusch

Publisher: Springer

Published: 2003-07-01

Total Pages: 281

ISBN-13: 3540365613

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This book presents 10 chapters on various aspects of intelligent information agents contributed by members of the respective AgentLink special interest group. The papers are organized in three parts on agent-based information systems, adaptive information agents, and coordination of information agents. Also included are a comprehensive introduction and surveys for each of the three parts.

Objective Coordination in Multi-Agent System Engineering
Objective Coordination in Multi-Agent System Engineering

Author: Michael Schumacher

Publisher: Springer

Published: 2001-04-25

Total Pages: 154

ISBN-13: 9783540419822

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Based on a suitably defined coordination model distinguishing between objective (inter-agent) coordination and subjective (intra-agent) coordination, this book addresses the engineering of multi-agent systems and thus contributes to closing the gap between research and applications in agent technology. After reviewing the state of the art, the author introduces the general coordination model ECM and the corresponding object-oriented coordination language STL++. The practicability of ECM/STL++ is illustrated by the simulation of a particular collective robotics application and the automation of an e-commerce trading system. Situated at the intersection of behavior-based artificial intelligence and concurrent and distributed systems, this monograph is of relevance to the agent R&D community approaching agent technology from the distributed artificial intelligence point of view as well as for the distributed systems community.

Multiagent Systems
Multiagent Systems

Author: Magdi S. Mahmoud

Publisher: CRC Press

Published: 2020-03-20

Total Pages: 330

ISBN-13: 1000078108

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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.

Field-Based Coordination for Pervasive Multiagent Systems
Field-Based Coordination for Pervasive Multiagent Systems

Author: Marco Mamei

Publisher: Springer Science & Business Media

Published: 2006-03-28

Total Pages: 243

ISBN-13: 3540279695

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More and more, software systems involve autonomous and distributed software components that have to execute and interact in open and dynamic environments, such as in pervasive, autonomous, and mobile applications. The requirements with respect to dynamics, openness, scalability, and decentralization call for new approaches to software design and development, capable of supporting spontaneous configuration, tolerating partial failures, or arranging adaptive reorganization of the whole system. Inspired by the behaviour of complex natural systems, scientists and engineers have started to adjust their mechanisms and techniques for self-organization and adaption to changing environments. In line with these considerations, Mamei and Zambonelli propose an interaction model inspired by the way masses and particles in our universe move and self-organize according to contextual information represented by gravitational and electromagnetic fields. The key idea is to have the components’ actions driven by computational force fields, generated by the components themselves or by some infrastructures, and propagated across the environment. Together with its supporting middleware infrastructure – available with additional information under http://www.agentgroup.unimore.it – this model can serve as the basis for a general purpose and widely applicable approach for the design and development of adaptive distributed applications.

Environments for Multi-Agent Systems
Environments for Multi-Agent Systems

Author: Danny Weyns

Publisher: Springer

Published: 2005-02-18

Total Pages: 288

ISBN-13: 3540322590

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The modern ?eld of multiagent systems has developed from two main lines of earlier research. Its practitioners generally regard it as a form of arti?cial intelligence (AI). Some of its earliest work was reported in a series of workshops in the US dating from1980,revealinglyentitled,“DistributedArti?cialIntelligence,”andpioneers often quoted a statement attributed to Nils Nilsson that “all AI is distributed. ” The locus of classical AI was what happens in the head of a single agent, and much MAS research re?ects this heritage with its emphasis on detailed modeling of the mental state and processes of individual agents. From this perspective, intelligenceisultimatelythepurviewofasinglemind,thoughitcanbeampli?ed by appropriate interactions with other minds. These interactions are typically mediated by structured protocols of various sorts, modeled on human conver- tional behavior. But the modern ?eld of MAS was not born of a single parent. A few - searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife). These scientists were impressed by the complex adaptive behaviors of commu- ties of animals (often extremely simple animals, such as insects or even micro- ganisms). The computational models on which they drew were often created by biologists who used them not to solve practical engineering problems but to test their hypotheses about the mechanisms used by natural systems. In the ar- ?cial life model, intelligence need not reside in a single agent, but emerges at the level of the community from the nonlinear interactions among agents. - cause the individual agents are often subcognitive, their interactions cannot be modeled by protocols that presume linguistic competence.

Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XV
Coordination, Organizations, Institutions, Norms, and Ethics for Governance of Multi-Agent Systems XV

Author: Nirav Ajmeri

Publisher: Springer Nature

Published: 2022-11-23

Total Pages: 241

ISBN-13: 3031208455

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This book constitutes the thoroughly refereed post-conference proceedings of the International Workshop on Coordination, Organizations, Institutions, and Norms for Governance of Multi-Agent Systems, COINE 2022, which was held in Auckland, New Zealand, on May 9, 2022. The 14 papers included in these proceedings were carefully reviewed and selected from 15 submissions. They deal with autonomous agents and multi-agent systems, focusing on the scientific and technological aspects of social coordination, organizational theory, artificial (electronic) institutions, and normative and ethical MAS.

Designing for Human-Machine Symbiosis Using the URANOS Model: Emerging Research and Opportunities
Designing for Human-Machine Symbiosis Using the URANOS Model: Emerging Research and Opportunities

Author: Hadorn, Benjamin

Publisher: IGI Global

Published: 2017-02-08

Total Pages: 186

ISBN-13: 1522518894

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Demand for integral and sustainable solutions is on the rise. As new ways of defining reality emerge, this generates the progression of more humanistic and sustainable construction of operating systems. Designing for Human-Machine Symbiosis Using the URANOS Model: Emerging Research and Opportunities is a pivotal reference source for the latest research on human-centered system modeling and methods to provide a generic system model to describe complex non-linear systems. Featuring extensive coverage across a range of relevant topics, such as pervasive computing systems, smart environments, and smart industrial machines, this book is ideally designed for researchers, engineers, and professionals seeking current research on the integration of human beings and their natural, informational, and socio-cultural environments into system design.

Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing
Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing

Author: Weiming Shen

Publisher: CRC Press

Published: 2019-09-17

Total Pages: 403

ISBN-13: 1482289253

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Agent Technology, or Agent-Based Approaches, is a new paradigm for developing software applications. It has been hailed as 'the next significant breakthrough in software development', and 'the new revolution in software' after object technology or object-oriented programming. In this context, an agent is a computer system which is capable of act

Engineering Environment-Mediated Multi-Agent Systems
Engineering Environment-Mediated Multi-Agent Systems

Author: Danny Weyns

Publisher: Springer Science & Business Media

Published: 2008-07-16

Total Pages: 306

ISBN-13: 3540850287

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Software intensive systems are increasingly expected to deal with changing user needs and dynamic operating conditions at run time. Examples are the need for life recon?gurations, management of resource variability, and dealing with p- ticular failure modes. Endowing systems with these kinds of capabilities poses severe challenges to software engineers and necessitates the development of new techniques, practices, and tools that build upon sound engineering principles. The ?eld of multi-agent systems focuses on the foundations and engineering of systems that consists of a network of autonomous entities (agents) that int- act to achieve the system goals. One line of research in multi-agent systems, inspired by biological, physical and other naturally occurring systems, concerns multi-agent systems in which agents share information and coordinate their - havior througha shared medium called an agentenvironment. Typical examples are gradient ?elds and digital pheromones that guide agents in their local c- text and as such facilitate the coordination of a community of agents. Since environment-mediation in multi-agent systems has shown to result in mana- able solutions with very adaptable qualities, it is a promising paradigm to deal with the increasing complexity and dynamism of distributed applications. Control in environment-mediated multi-agent systems is decentralized, i. e. , noneofthecomponentshasfullaccessorcontroloverthesystem. Self-organization isanapproachtoengineerdecentralized,distributedandresource-limitedsystems thatarecapableofdynamicallyadaptingtochangingconditionsandrequirements without external intervention. This useful system property is often re?ected in functionssuchasself-con?guration,self-optimization,andself-healing. Engine- ing approaches to self-organizing systems often rely on global functionality to emerge from localand autonomous decisions of individual agents that commu- catethroughasharedagentenvironment.