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The Interaction Effort in Autonomous Logistics Processes: Potential and Limitations for Cooperation

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Autonomous Cooperation and Control in Logistics

Abstract

Autonomous control in logistics decreases the computational effort for process control by problem decomposition. To this end, decision-making is delegated to the participating logistics entities. The more process control is decentralised the more interaction effort arises for coordinating the participants for efficient resource utilisation. This increase in interaction effort might even outweigh the decrease in computational effort gained by decomposition. Therefore, it is necessary to reduce the interaction effort by adequate organisational structures. Team formation as a prerequisite for establishing these structures, however, also requires interaction effort. Hence, this chapter analytically narrows the optimal degree at which autonomous control is applied by the interaction effort arising for individual and team action as well as team formation.

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References

  1. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Network 38(4):393–422

    Article  Google Scholar 

  2. Berndt JO (2011) Self-organizing supply networks: autonomous agent coordination based on expectations. In: ICAART 2011, INSTICC Press, Rome, Italy

    Google Scholar 

  3. Brauer W, Nickles M, Rovatsos M, Weiß G, Lorentzen KF (2002) Expectation-oriented analysis and design. In: AOSE 2001, Springer, Montreal, QC, Canada, pp 226–244

    Google Scholar 

  4. Collins J, Youngdahl B, Jamison S, Mobasher B, Gini M (1998) A market architecture for multi-agent contracting. In: Agents 1998, ACM Press, Saint Paul, MN, USA, pp 285–292

    Google Scholar 

  5. Dignum R, Dunin-Keplicz B, Verbrugge R (2000) Agent theory for team formation by dialogue. In: ATAL 2000, Springer, Boston, MA, USA, pp 150–166

    Google Scholar 

  6. Ferber J, Gutknecht O (1998) A meta-model for the analysis and design of organizations in multi-agent systems. In: ICMAS 1998, IEEE Computer Society, Paris, France, pp 128–135

    Google Scholar 

  7. Fischer K, Schillo M, Siekmann JH (2003) Holonic multiagent systems: a foundation for the organisation of multiagent systems. In: HoloMAS 2003, Springer, Prague, Czech Republic,pp 71–80

    Google Scholar 

  8. Fischer K, Florian M, Malsch T (eds) (2005) Socionics. Scalability of complex social systems. Springer, Heidelberg, Germany

    Google Scholar 

  9. Gehrke JD (2009) Evaluating situation awareness of autonomous systems. In: Madhavan R, Tunstel E, Messina E (eds) Performance evaluation and benchmarking of intelligent systems. Springer, Heidelberg, Germany, pp 93–111

    Chapter  Google Scholar 

  10. Hannoun M, Boissier O, Sichman JS, Sayettat C (2000) MOISE: an organizational model for multi-agent systems. In: IBERAMIA-SBIA 2000, Springer, Atibaia, Brazil, pp 156–165

    Google Scholar 

  11. Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In: HICSS 2000, IEEE Computer Society, Maui, Hawaii, vol 8, pp 8020–8029

    Google Scholar 

  12. Hülsmann M, Windt K (eds) (2007) Understanding autonomous cooperation and control in logistics. Springer, Heidelberg, Germany

    Google Scholar 

  13. Horling B, Lesser V (2005) A survey of multi-agent organizational paradigms. Knowl Eng Rev 19(4):281–316, URL http://mas.cs.umass.edu/paper/366

  14. Langer H, Gehrke JD, Hammer J, Lorenz M, Timm IJ, Herzog O (2006) A framework for distributed knowledge management in autonomous logistic processes. Int J Knowl Base Intell Eng Syst 10(4):277–290

    Google Scholar 

  15. Luhmann N (1995) Social systems. Stanford University Press, Stanford

    Google Scholar 

  16. MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: 5th Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, Berkeley, CA, USA, pp 281–296

    Google Scholar 

  17. Montgomery TA, Durfee EH (1993) Search reduction in hierarchical distributed problem solving. Group Decis Negot 2:301–317

    Article  Google Scholar 

  18. Nickles M, Weiss G (2005) Multiagent systems without agents – mirror-holons for the compilation and enactment of communication structures. In: Fischer K, Florian M, Malsch T (eds) (2005) Socionics. Scalability of complex social systems. Springer, Heidelberg, Germany,pp 263–288

    Google Scholar 

  19. Nickles M, Rovatsos M, Weiss G (2005) Expectation-oriented modeling. Eng Appl Artif Intell 18(8):891–918, DOI DOI:10.1016/j.engappai.2005.05.002, URL http://www.sciencedirect.com/science/article/B6V2M-4GJK86T-1/%2/74b3c8947f7310792c5a5cb3235a091d

    Google Scholar 

  20. Ogston E, Vassiliadis S (2001) Matchmaking among minimal agents without a facilitator. In: Agents 2001, ACM, Montreal, QC, Canada, pp 608–615

    Google Scholar 

  21. Rosenschein JS, Zlotkin G (1994) Rules of encounter: designing conventions for automated negotiation among computers. MIT, Cambridge, MA, USA

    Google Scholar 

  22. Sandholm TW (1999) Distributed rational decision making. In: Weiss G (ed) Multiagent systems. A modern approach to distributed artificial intelligence, MIT, Cambridge, MA, USA,pp 201–258

    Google Scholar 

  23. Schillo M, Spresny D (2005) Organization: the central concept for qualitative and quantitative scalability. In: Fischer K, Florian M, Malsch T (eds) (2005) Socionics. Scalability of complex social systems. Springer, Heidelberg, Germany, pp 84–103

    Google Scholar 

  24. Schillo M, Fischer K, Fley B, Florian M, Hillebrandt F, Spresny D (2004) FORM – A sociologically founded framework for designing self-organization of multiagent systems. In: RASTA 2002, Springer, Bologna, Italy, pp 156–175

    Google Scholar 

  25. Schuldt A (2009) Decentralisation and interaction efficiency in cooperating autonomous logistics processes. In: LDIC 2009, Springer, Bremen, Germany

    Google Scholar 

  26. Schuldt A (2010) Multiagent coordination enabling autonomous logistics. Doctoral dissertation, Universität Bremen, Germany

    MATH  Google Scholar 

  27. Schuldt A (2011) Team formation for agent cooperation in logistics: protocol design and complexity analysis. In: ICAART 2011, INSTICC Press, Rome, Italy

    Google Scholar 

  28. Schuldt A, Werner S (2007) Towards autonomous logistics: conceptual, spatial, and temporal criteria for container cooperation. In: LDIC 2007, Springer, Bremen, Germany, pp 311–319

    Google Scholar 

  29. Smith RG (1977) The contract net: a formalism for the control of distributed problem solving. In: IJCAI 1977, William Kaufmann, Cambridge, MA, USA, p 472

    Google Scholar 

  30. Timm IJ, Knirsch P, Kreowski HJ, Timm-Giel A (2007) Autonomy in software systems. In: Hülsmann M, Windt K (eds) (2007) Understanding autonomous cooperation and control in logistics. Springer, Heidelberg, Germany, pp 255–273

    Google Scholar 

  31. Windt K (2008) Ermittlung des angemessenen Selbststeuerungsgrades in der Logistik – Grenzen der Selbststeuerung. In: Nyhuis P (ed) Beitrge zu einer Theorie der Logistik, Springer, Heidelberg, Germany, pp 349–372

    Chapter  Google Scholar 

  32. Windt K, Hülsmann M (2007) Changing paradigms in logistics. In: Hülsmann M, Windt K (eds) (2007) Understanding autonomous cooperation and control in logistics. Springer, Heidelberg, Germany, pp 1–16

    Google Scholar 

  33. Wooldridge M, Jennings NR (1995) Intelligent agents: theory and practice. Knowl Eng Rev 10(2):115–152

    Article  Google Scholar 

  34. Wooldridge M, Jennings NR (1999) The cooperative problem solving process. J Logic Comput 9(4):563–592

    Article  MathSciNet  Google Scholar 

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Correspondence to Arne Schuldt .

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Schuldt, A., Berndt, J.O., Herzog, O. (2011). The Interaction Effort in Autonomous Logistics Processes: Potential and Limitations for Cooperation. In: Hülsmann, M., Scholz-Reiter, B., Windt, K. (eds) Autonomous Cooperation and Control in Logistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19469-6_7

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  • DOI: https://doi.org/10.1007/978-3-642-19469-6_7

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