Presents a methodology developed by DaimlerChrysler.
Illustrates the methodology through detailed case studies.
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Stefan Bussmann studied computer science at the University of Kaiserslautern, Germany, and at the Institut National Polytechnique de Grenoble, France. He received a PhD degree from the University of Southampton, UK, in 2003. Since 1993 he is with the DaimlerChrysler Research and Technology in Berlin, where he is working as a senior scientist on innovative production planning and control methods. He has published several papers on agent-based manufacturing control and has brought into operation the probably first full-scale industrial agent-based manufacturing control system.
Nick Jennings is Professor of Computer Science in the 5*-rated School of Electronics and Computer Science at Southampton University where he carries out basic and applied research in agent-based computing. He has published some 200 articles and 6 books on various facets of agent-based computing and holds 2 patents (3 more pending). He is in the top 125 most cited computer scientists (out of 660,000) according to the CiteSeer digital library and has received a number of awards for his research: the Computers and Thought Award (the premier award for a young AI scientist) in 1999 (this is the only time in the Award's 30 year history that it has been given to someone based in Europe), an IEE Achievement Medal in 2000, and the ACM Autonomous Agents Research Award in 2003.
Michael Wooldridge is Professor of Computer Science at the University of Liverpool, UK, where he is currently Head of Department. His main research interests are in the use of formal methods for reasoning about multiagent systems. He has published more than 150 articles and 13 books on multiagent systems, including a research monograph (Reasoning about Rational Agents, 2000) and an introductory textbook (An Introduction to Multiagent Systems, 2002). He is currently editor-in-chief of the journal Autonomous Agents and Multiagent Systems.
The ability of production companies to rapidly develop and deploy effective and efficient control systems is critical for success in the consumer-driven environment of contemporary manufacturing. This book presents a novel approach to the design of manufacturing control systems, based around the idea of agents, semiautonomous decision makers that cooperate to process goods and meet orders. This new methodology is DACS Designing Agent-based Control Systems.
Developed at DaimlerChrysler s research labs in Berlin, DACS is the first methodology specifically produced for the design of agent-based control systems. Beginning with a detailed overview of agent technologies, manufacturing control, and design methodologies, the book explains the DACS methodology and illustrates it by way of detailed case studies. The book will be of interest to researchers and practitioners in agent systems, manufacturing control, and software methodologies.
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