Multiagent Systems for Manufacturing Control A Design Methodology
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 ide...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2004, 2004
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| Edition: | 1st ed. 2004 |
| Series: | Springer Series on Agent Technology
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Introduction
- 2 Agent-Based Production Control
- 3 Design Methodologies
- 4 The DACS Methodology for Production Control
- 5 Evaluation of the DACS Methodology
- 6 Conclusion
- Appendix A. Example Characterisations
- A.1 Voting
- A.1.1 The plurality voting protocol
- A.1.2 The Clarke tax protocol
- A.2 Negotiation
- A.2.1 Service-oriented negotiation
- A.2.2 The monotonic concession protocol
- A.2.3 The DECIDE conflict resolution protocol
- A.3 Auctions
- A.3.1 The English auction
- A.3.2 The contract-net protocol
- A.3.3 The continuous double auction
- A.4 Distributed constraint satisfaction
- A.4.1 Asynchronous backtracking search
- A.5 Coalition formation
- A.6 Co-ordination of multi-agent plans
- A.6.1 Partial global planning
- A.6.2 Generalised partial global planning
- A.6.3 Consensus-based distributed planning
- A.7 Application-specific interaction protocols
- A.7.1 Kowest work-in-process control protocol
- A.8 Simple interaction protocols
- A.8.1 Requesting action
- A.9 Social laws
- Appendix B. Industrial Test Case
- B.1 Specification of the production control problem
- B.1.1 Production system
- B.1.2 Production operation conditions
- B.1.3 Control interfaces
- B.1.4 Production goals and requirements
- B.2 Analysis of decision making
- B.2.1 Identification of effectoric decisions
- B.2.2 Identification of decision dependencies
- B.3 Identification of agents
- B.3.1 Improving the decision model
- B.3.2 Clustering of decision tasks
- B.4 Selection of interaction protocols
- B.4.7 Summary
- B.5 Results from the test case
- B.6 Summary of the test case
- Appendix C. Third-Party Reviews
- C.1 Review by Ilka Lehweß-Litzmann
- C.2 Review by Laura Obretin
- C.3 Review by Schneider Electric
- C.4 Review by the DaimlerChrysler
- List of Figures
- List of Tables.-References