Traditional manufacturing systems rely upon centralized, hierarchical systems that are not responsive enough to the increasing demand for mass customization. Decentralized, or heterarchical, management systems using autonomous agents promise to nullify the limitations of previous solutions. Agent-Based Manufacturing and Control Systems: New

Low-volume high-variety products like personalized cars or customized engines will be the key issues for manufacturing in the 21st century. The necessary control technology is based on the concept of holons, which are the units of production and behave as autonomous and cooperative agents, providing flexibility, adaptability, agility, and dynamic reconfigurability. This book presents the latest research results in agent-based manufacturing as carried out by researchers in academia and industry within the international "Holonic Manufacturing Systems" project. As this project was driven by industry, the results presented here are of vital interest not just to researchers in agent technologies or distributed artificial intelligence, but also to engineers and professionals in industry who have to respond to rapid changes and new demands in production.

At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent based methods for today’s competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation. Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent based production planning and control Written by an author with more than 20 years’ experience in studying and formulating a complete theoretical system in production planning technologies Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis Comprehensive and concise, Multi-Agent Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.

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 acting autonomously in its environment in order to meet its design objectives. So in the area of concurrent design and manufacturing, a manufacturing resource, namely a machine or an operator, may cooperate and negotiate with other agents for task assignment; and an existing engineering software can be integrated with a distributed integrated engineering design and manufacturing system. Hence in agent-based systems, there is no centralized system control structure, and no pre-defined agenda for the system execution, as exist in traditional systems. This book systematically describes the principles, key issues, and applications of agent technology in relation to concurrent engineering design and manufacturing. It introduces the methodology, standards, frameworks, tools, and languages of agent-based approaches and presents a general procedure for building agent-based concurrent engineering design and manufacturing systems. Both professional and university researchers and postgraduates should find this an invaluable presentation of the corresponding theories and methods, with some practical examples for developing multi-agent systems in the domain.

A comprehensive and hands-on introduction to the core concepts, methods, and applications of agent-based modeling, including detailed NetLogo examples. The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach—with hundreds of examples and exercises using NetLogo—enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code.

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.

Presents a methodology developed by DaimlerChrysler. Illustrates the methodology through detailed case studies.