Skip to main content
SpringerLink
Log in

Collaborative Agent Tuning: Performance Enhancement on Mobile Devices

  • Conference paper
Engineering Societies in the Agents World VI (ESAW 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3963))

Included in the following conference series:

Abstract

Ambient intelligence envisages a world saturated with sensors and other embedded computing technologies, operating transparently, and accessible to all in a seamless and intuitive manner. Intelligent agents of varying capabilities may well form the essential constituent entities around which this vision is realized. However, the practical realization of this vision will severely exacerbate the complexity of existing software solutions, a problem that autonomic computing was originally conceived to address. Thus we can conjecture that the incorporation of autonomic principles into the design of Multi-Agent Systems is indeed a desirable objective. As an illustration of how this may be achieved, a strategy termed Collaborative Agent Tuning is described, which seeks to optimise agent performance on computationally limited devices. A classic mobile computing application is used to illustrate the principles involved.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing. IEEE Computer 36(1), 41–50 (2003)

    Google Scholar 

  2. Aarts, E., Marzano, S. (eds.): The New Everyday: Views on Ambient Intelligence. 010 Publishers, Rotterdam (2003)

    Google Scholar 

  3. O’Grady, M.J., O’Hare, G.M.P.: Just-in-Time Multimedia Distribution in a Mobile Computing Environment. IEEE Multimedia 11(4), 62–74 (2004)

    Article  Google Scholar 

  4. Rao, A.S., Georgeff, M.P.: Modelling Rational Agents within a BDI Architecture. In: Principles of Knowledge Representation & Reasoning, San Mateo, CA (1991)

    Google Scholar 

  5. O’Hare, G.M.P., O’Grady, M.J.: Gulliver’s Genie: A Multi-Agent System for Ubiquitous and Intelligent Content Delivery. Computer Communications 26(11), 1177–1187 (2003)

    Article  Google Scholar 

  6. Keegan, S., O’Hare, G.M.P.: EasiShop – Agent-Based Cross Merchant Product Comparison Shopping for the Mobile User. In: Proceedings of 1st International Conference on Information & Communication Technologies: From Theory to Applications (ICTTA 2004), Damascus, Syria (2004)

    Google Scholar 

  7. Strahan, R., O’Hare, G.M.P., Phelan, D., Muldoon, C., Collier, R.: ACCESS: An Agent based Architecture for the Rapid Prototyping of Location Aware Services. In: Proceedings of the 5th International Conference on Computational Science (ICCS 2005), Emory University Atlanta, USA (2005)

    Google Scholar 

  8. Soh, L.-K., Tsatsoulis, C.: Agent-Based Argumentative Negotiations with Case-Based Reasoning. In: AAAI Fall Symposium Series on Negotiation Methods for Autonomous Cooperative Systems, North Falmouth, Mass, pp. 16–25 (2001)

    Google Scholar 

  9. Groth, P.T., Suri, N.: CPU Resource Control and Accounting in the NOMADS Mobile Agent System, Technical Report, Institute for Human & Machine Cognition, University of West Florida (2002)

    Google Scholar 

  10. Bigus, J.P., Hellerstein, J.L., Squillante, M.S. Auto Tune: A Generic Agent for Automated Performance Tuning, Proceedings of the International Conference on Practical Application of Intelligent Agents and Multi-Agents (PAAM), 2000.

    Google Scholar 

  11. Bigus, J.P., Schlosnagle, D.A., Pilgrim, J.R., Mills III, W.N., Diao, Y.: ABLE: A Toolkit for Building Multiagent Autonomic Systems. IBM Systems Journal 41(3), 350–371 (2002)

    Article  Google Scholar 

  12. Liu, H., Parashar, M.: DIOS++: A Framework for Rule-Based Autonomic Management of Distributed Scientific Applications. In: Kosch, H., Böszörményi, L., Hellwagner, H. (eds.) Euro-Par 2003. LNCS, vol. 2790, pp. 66–73. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  13. Walsh, W.E., Wellman, M.P.: A market protocol for decentralized task allocation: Extended version. In: Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS 1998) (1998)

    Google Scholar 

  14. Cohen, P.R., Levesque, H.J.: Intention Is Choice with Commitment. Artificial Intelligence 42, 213–261 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  15. Levesque, H.J., Cohen, P.R., Nunes, J.H.T.: On Acting Together. In: Proceedings of AAAI 1990, pp. 94–99 (1990)

    Google Scholar 

  16. Singh, M.P.: A Social Semantics for Agent Communication Languages. In: Dignum, F.P.M., Greaves, M. (eds.) Issues in Agent Communication. LNCS, vol. 1916, pp. 31–45. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  17. Tarkoma, S., Laukkanen, M.: Supporting Software Agents on Small Devices. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002), Bologna, Italy (July 2002)

    Google Scholar 

  18. Foundation for Intelligent Physical Agents (FIPA), http://www.fipa.org

  19. Johansen, D., Lauvset, K., Van Renesse, R., Schneider, F., Sudmann, N., Jacobsen, K.: A Tacoma Retrospective. Software Practice and Experience 32(6), 605–619 (2002)

    Article  MATH  Google Scholar 

  20. Bergenti, F., Poggi, A.: LEAP: A FIPA Platform for Handheld and Mobile Devices. In: Meyer, J.-J.C., Tambe, M. (eds.) ATAL 2001. LNCS, vol. 2333, p. 436. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  21. The Agent Oriented Software Group, http://www.agent-software.com

  22. Koch, F., Meyer, J.-J.C., Dignum, F.P.M., Rahwan, I.: Programming deliberative agents for mobile services: The 3APL-M platform. In: Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A. (eds.) PROMAS 2005. LNCS, vol. 3862, pp. 222–235. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  23. Rahwan, T., Rahwan, T., Rahwan, I., Ashri, R.: Agent-Based Support for Mobile Users Using AgentSpeak(L). In: Giorgini, P., Henderson-Sellers, B., Winikoff, M. (eds.) AOIS 2003. LNCS (LNAI), vol. 3030, pp. 45–60. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  24. O’Hare, G.M.P.: Agent Factory: An Environment for the Fabrication of Multi-Agent Systems. In: O’Hare, G.M.P., Jennings, N. (eds.) Foundations of Distributed Artificial Intelligence, pp. 449–484. John Wiley and Sons Inc., Chichester (1996)

    Google Scholar 

  25. Collier, R., O’Hare, G.M.P., Lowen, T., Rooney, C.: Beyond Prototyping in the Factory of Agents. In: Mařík, V., Müller, J.P., Pěchouček, M. (eds.) CEEMAS 2003. LNCS, vol. 2691, p. 383. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  26. Jennings, N.R.: Controlling Cooperative Problem Solving in Industrial Multi-Agent Systems using Joint Intentions. Artificial Intelligence 75(2), 195–240 (1995)

    Article  Google Scholar 

  27. Kumar, S., Cohen, P.R., Levesque, H.J.: The Adaptive Agent Architecture: Achieving Fault-Tolerance Using Persistent Broker Teams. In: Proceedings of Fourth International Conference on Multi-Agent Systems (ICMAS 2000), Boston, MA, pp. 159–166. IEEE Press, Los Alamitos (2000a)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Practice & Research in Intelligent Systems & Media (PRISM) Laboratory, School of Computer Science & Informatics, University College Dublin (UCD), Belfield, Dublin 4, Ireland

    Conor Muldoon

  2. Adaptive Information Cluster (AIC), School of Computer Science & Informatics, University College Dublin (UCD), Belfield, Dublin 4, Ireland

    Gregory M. P. O’Hare & Michel J. O’Grady

Authors
  1. Conor Muldoon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregory M. P. O’Hare
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michel J. O’Grady
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, Ege University, 35100, Bornova, Izmir, Turkey

    Oğuz Dikenelli

  2. IRIT – Paul Sabatier University, 118, Route de Narbonne, 31062, Toulouse, Cedex 9, France

    Marie-Pierre Gleizes

  3. DEIS, Alma Mater Studiorum, Università di Bologna, Italy

    Alessandro Ricci

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Muldoon, C., O’Hare, G.M.P., O’Grady, M.J. (2006). Collaborative Agent Tuning: Performance Enhancement on Mobile Devices. In: Dikenelli, O., Gleizes, MP., Ricci, A. (eds) Engineering Societies in the Agents World VI. ESAW 2005. Lecture Notes in Computer Science(), vol 3963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759683_15

Download citation

  • DOI: https://doi.org/10.1007/11759683_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34451-3

  • Online ISBN: 978-3-540-34452-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation