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Industrial Agents

Industrial Agents
  • Author : Paulo Leitão,Stamatis Karnouskos
  • Publisher : Morgan Kaufmann
  • Release : 13 March 2015
GET THIS BOOKIndustrial Agents

Industrial Agents explains how multi-agent systems improve collaborative networks to offer dynamic service changes, customization, improved quality and reliability, and flexible infrastructure. Learn how these platforms can offer distributed intelligent management and control functions with communication, cooperation and synchronization capabilities, and also provide for the behavior specifications of the smart components of the system. The book offers not only an introduction to industrial agents, but also clarifies and positions the vision, on-going efforts, example applications, assessment and roadmap applicable to


Industrial Agents

Industrial Agents
  • Author : Paulo Leitão,Stamatis Karnouskos
  • Publisher : Morgan Kaufmann
  • Release : 13 March 2015
GET THIS BOOKIndustrial Agents

Industrial Agents explains how multi-agent systems improve collaborative networks to offer dynamic service changes, customization, improved quality and reliability, and flexible infrastructure. Learn how these platforms can offer distributed intelligent management and control functions with communication, cooperation and synchronization capabilities, and also provide for the behavior specifications of the smart components of the system. The book offers not only an introduction to industrial agents, but also clarifies and positions the vision, on-going efforts, example applications, assessment and roadmap applicable to


Industrial Applications of Holonic and Multi-Agent Systems

Industrial Applications of Holonic and Multi-Agent Systems
  • Author : Vladimír Mařík,Jose Luis Martinez Lastra,Petr Skobelev
  • Publisher : Springer
  • Release : 21 August 2013
GET THIS BOOKIndustrial Applications of Holonic and Multi-Agent Systems

This book constitutes the refereed proceedings of the 6th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2013, held in Prague, Czech Republic, in August 2013, in conjunction with DEXA 2013. The 25 revised full papers presented together with two invited talks were carefully reviewed and selected from 37 submissions. The papers are organized in the following topical sections: MAS in automation and manufacturing; design, simulation and validation; MAS in transportation systems; industrial applications; and new trends.


IP Network-based Multi-agent Systems for Industrial Automation

IP Network-based Multi-agent Systems for Industrial Automation
  • Author : David P. Buse,Q.H. Wu
  • Publisher : Springer Science & Business Media
  • Release : 23 February 2007
GET THIS BOOKIP Network-based Multi-agent Systems for Industrial Automation

This book details the use of the Internet protocol suite and multi-agent systems for the information management, online monitoring, and control of distributed power system substations. It proposes an open architecture for information management and control, based on the concepts of multi-agent systems and mobile agents. Mobile agents are applied to the retrieval and analysis of substation data and to remote operator intervention.





Handbook of Chemical and Biological Warfare Agents

Handbook of Chemical and Biological Warfare Agents
  • Author : D. Hank Ellison
  • Publisher : CRC Press
  • Release : 24 August 2007
GET THIS BOOKHandbook of Chemical and Biological Warfare Agents

Extensively revised and updated, this second edition of the bestselling Handbook of Chemical and Biological Warfare Agents goes well beyond thedirty thirty commonly discussed agents and provides rapid access to a wide range of agents that can be used as weapons. This edition incorporates additional classes of agents, expands existing clas




Smart Agents for the Industry 4.0

Smart Agents for the Industry 4.0
  • Author : Max Hoffmann
  • Publisher : Springer Nature
  • Release : 11 September 2019
GET THIS BOOKSmart Agents for the Industry 4.0

Max Hoffmann describes the realization of a framework that enables autonomous decision-making in industrial manufacturing processes by means of multi-agent systems and the OPC UA meta-modeling standard. The integration of communication patterns and SOA with grown manufacturing systems enables an upgrade of legacy environments in terms of Industry 4.0 related technologies. The added value of the derived solutions are validated through an industrial use case and verified by the development of a demonstrator that includes elements of self-optimization through Machine Learning




Holonic and Multi-Agent Systems for Manufacturing

Holonic and Multi-Agent Systems for Manufacturing
  • Author : Vladimír Mařík,Pavel Vrba,Paulo Leitão
  • Publisher : Springer Science & Business Media
  • Release : 19 August 2011
GET THIS BOOKHolonic and Multi-Agent Systems for Manufacturing

This book constitutes the refereed proceedings of the 5th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2011, held in Toulouse, France, August 29-31, 2011. The 25 revised full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on industrial agents, simulation and modelling, planning and scheduling, smart technical systems, and MAS for unmanned aerial vehicles.


Smart Agents for the Industry 4.0

Smart Agents for the Industry 4.0
  • Author : Max Hoffmann
  • Publisher : Springer Vieweg
  • Release : 27 September 2020
GET THIS BOOKSmart Agents for the Industry 4.0

Max Hoffmann describes the realization of a framework that enables autonomous decision-making in industrial manufacturing processes by means of multi-agent systems and the OPC UA meta-modeling standard. The integration of communication patterns and SOA with grown manufacturing systems enables an upgrade of legacy environments in terms of Industry 4.0 related technologies. The added value of the derived solutions are validated through an industrial use case and verified by the development of a demonstrator that includes elements of self-optimization through Machine Learning