Skip to main content

Outline of Modification Systems

  • Chapter
Knowledge-Driven Computing

Summary

This paper tries to understand the keys necessary for a new approach for automatic control. It starts by analyzing its history and identifying the symptoms that occur once and again when new paradigms, theories or breakthrough inventions came up. Then, it analyses the symptoms of today and discusses whether they match any of the previous symptoms in the past. Then, yet another theory is proposed here, the modification systems, which joins the benefits of Automatic Control and Agents Metaphor: The modification systems, which are designed as a generalization of control systems and situated agents, where anybody does not control a system but modifies a system by some multidimensional change of its original behavior toward a desired target behavior. We show some examples and case studies of their behavior, which as a potential generalization of automatic control give the background to conceive further tools to design more simple but powerful controllers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zahed L (1996) The Evolution of Systems Analysis and Control: A Personal Perspective. IEEE Control Systems Magazine, June 1996, pp. 95–98

    Google Scholar 

  2. Luck M, McBurne P, Shehory O, Willmott S (2005) Agent Technology: Computing as Interaction. A Roadmap for Agent Based Computing, Compiled, written and edited by M. Luck, P. McBurney, O. Shehory, S. Willmott and the AgentLink Community

    Google Scholar 

  3. Bennet S (1996) A Brief History of Automatic Control. IEEE Control Systems Magazine, June 1996, pp. 17–25

    Google Scholar 

  4. Murray R, Astrom KJ, Boyd S, Brockett RW, Stein G (2003) Future Directions in Control in an Information-Rich World. IEEE Control Systems Magazine, Apr. 2003, vol. 23, no. 2, pp. 20–33. Previous version Available: http://www.cds.caltech.edu/~murray/cdspanel

  5. Halang WA, Sanz R, Babuska R, Roth H (2005) Information and Communication Technology Embraces Control. Status Report prepared by the IFAC Coordinating Committee on Computers, Cognition and Communication, World IFAC Congress

    Google Scholar 

  6. Asada M, Kuniyoshi Y, et al. (1997) The RoboCup Physical Agent Challenge. First RoboCup Workshop in the XV IJCAI-97 International Joint Conference on Artificial Intelligence, pp. 51–56, http://www.robocup.org

  7. Wooldridge M, Jennings NR (1995) Intelligent Agents: Theory and Practice. The Knowledge Engineering Review, vol. 10:2, pp. 115–152

    Article  Google Scholar 

  8. Sanz R, Escasany J, López I (2001) Systems and Consciousness. In: Proc. Conf. Towards a Science of Consciousness (TSC)

    Google Scholar 

  9. Sanz R, Holland O, Sloman A, Kirilyuk A, Edmondson W, Torrance S. (2005) Self-aware Control Systems. Research Whitepaper for the Bioinspired Intelligent Information Systems Call, IFAC 2005

    Google Scholar 

  10. Brooks RA (1991) A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, 2 (1), pp. 14–23, 1987. And a new version in: Brooks RA “New Approaches to Robotics”. Science, vol. 253, September 1991, pp. 1227–1232

    Google Scholar 

  11. Jennings NR, Bussmann S (2003) Agent-Based Control Systems. Why Are They Suited to Engineering Complex Systems? IEEE Control Systems Magazine, Jun. 2003, vol. 23, no. 3, pp. 61–73

    Article  Google Scholar 

  12. Hall KH, Staron RJ, Vrba P. (2005) Experience with Holonic and Agent-Based Control Systems and Their Adoption by Industry. Holonic and Multi-Agent Systems for Manufacturing, vol. 3593/2005, pp. 1–10

    Article  Google Scholar 

  13. Ibarra S, Quintero MC, Busquets D, Ramón J, de la Rosa J, Castán J. (2006) Improving the Team-work in Heterogeneous Multiagent Systems. Situation Matching Approach. Frontiers in Artificial Intelligence and Applications - AI Research and Development, ISSN 0922-6389, vol. 146, pp. 275–282, October 2006, IOS Press

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

de la Rosa, J.L., Figueras, A., Quintero, C., Ramon, J.A., Ibarra, S., Esteva, S. (2008). Outline of Modification Systems. In: Cotta, C., Reich, S., Schaefer, R., Ligęza, A. (eds) Knowledge-Driven Computing. Studies in Computational Intelligence, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77475-4_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-77475-4_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77474-7

  • Online ISBN: 978-3-540-77475-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics