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Purposive behavior of honeybees as the basis of an experimental search engine

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Abstract

The foraging behavior of active honeybee colonies serves as a model for Web explorers that are reactive, proactive, and robust. The Web explorers are developed to forage a simulated information ecosystem—the Internet—for useful information. Each explorer is designed to detect and report dynamic changes within the infrastructure of the Internet to its Web explorer dispatcher, which is responsible for coordinating thousands of explorers. Experimental results are presented.

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References

  1. Anderson D, Bansal D, Curtis D, Seshan S, Balakrishnan H (2000) System support for bandwidth management and content adaption in internet applications. In: OSDI 2000: Proceedings of fourth USENIX symposium on operating system design and implementation, ACM Press

  2. Bagrodia R (1989) Process synchronization: design and performance evaluation of distributed algorithms. IEEE Trans Softw Eng 15(9):1053–1064

    Article  Google Scholar 

  3. Berners-Lee T, Cailliau R, Groff J, Pollermann B (1992) World-Wide Web: the information Universe. Electron Netw Res Appl Policy 1(1):74–82

    Google Scholar 

  4. Braden B, Cerpa A, Faber T, Lindell B, Phillips G, Kann J (1999) The ASP EE: an active execution environment for network control protocols. Tech. rep., Information Sciences Institute, University of Southern California, Marina del Rey, California

  5. Clark O, Kok R (1995) The study of ecosystem dynamics using simulation. For presentation to the Canadian Society of Agricultural Institute of Canada Annual Conference, 9–12 July 1995, Ottawa. CSAE Paper No. 95–606

  6. Collins R, Jefferson D (1991) AntFarm: towards simulated evolution. In: Framer J, Langton C, Rasmussen S, Taylor C (eds) Artificial life (II). Addison-Wesley, Redwood City, pp 579–601

    Google Scholar 

  7. Dill S, Kumar R, McCurley K, Rajagopalan S, Sivakumar D, Tomkins A (2002) Self-similarity in the Web. ACM Transa Internet Technol (TOIT) 2(3):205–223

    Article  Google Scholar 

  8. Dornhaus A, Klugl F, Puppe F, Tautz J (1998) Task Selection in honeybees—experiments using multi-agent simulation. In: Wilke C, Altmeyer S, Martinez T (eds) 3rd German workshop on artificial life. Verlag Harri Deutsch, pp 171–183

  9. von Eicken T, Culler D, Goldstein SC, Schauser K (1992) Active messages: a mechanism for integrated communication and computation. In: Proceedings of 19th annual international symposium on computer architecture, pp 256–266

  10. Fraser A (1968) The evolution of purposive behavior. In: von Foerster H, White J, Peterson L, Russell J (eds) Purposive systems. Spartan Books, pp 15–23

    Google Scholar 

  11. Fritsch P (2000) Five mellow guys follow their dream: A ‘Tall Ship’ in Brazil. Wall Street Journal (Western Edition) CXLII(35):Sect A:1 (Col. 4)

  12. Jung J, Sit E, Balakrishnan H, Morris R (2001) DNS performance and the Effectiveness of cachingIn: Proceedings of the first ACM SIGComm workshop on internet measurement. ACM Press, pp 153–167

  13. Lachmann M, Sella G, Jablonka E (2000) On the advantages of information sharing. Proc R Soc Lond B 267:1287–1293

    Article  Google Scholar 

  14. Li L, Martinoli A, Abu-Mostafa Y (2002) Emergent specialization in swarm systems. In: Yin H, Allinson N, Freeman R, Keane J, Hubbard S (eds) IDEAL 2002: Proceedings of the intelligent data engineering and automated learning conference, LNCS, Vol 2412. Springer, Berlin Heidelberg Network, pp 261–266

    Google Scholar 

  15. Merugu S, Bhattacharjee S, Chae Y, Sanders M, Calvert K, Zegura E (1999) Bowman and CANEs: Implementation of an active network. In: Proceedings of the 37th annual Allerton conference on communication, control, and computing

  16. Michtchenko A (2000) Search-for-service strategy and integration of LAN into Web operating system. In: Proceedings of HPC 2000. SCS Press, pp 231–235

  17. Myllymaki J (2002) Effective Web Data extraction with standard XML technologies. Comput Netw 39:635–644

    Article  Google Scholar 

  18. Oates M, Corne D (2001) Global Web server load balancing using evolutionary computational techniques. soft comput 5:297–312

    Article  MATH  Google Scholar 

  19. Oida K, Sekido M (1999) An agent-based routing system for QoS guarantees. In: Proceedings of the IEEE on systems, man, and cybernetics. IEEE, pp 833–838

  20. Saxena P, Choudhury D, Gabrani G, Gupta S, Bhardwaj M, Chopra M (2002) A heuristic approach to resource locations in broadband networks. J Netw Comput Appl 25:1–35

    Article  Google Scholar 

  21. Srivastava A, Han E, Kumar V, Singh V (1999) Parallel formulations of decision-tree classification algorithms. Data Min Knowl Discov 3(3):237–261

    Article  Google Scholar 

  22. Sumpter D, Pratt S (2003) A modelling framework for understanding social insect foraging. Behav Ecol Sociobiol 53:131–144

    Google Scholar 

  23. Vasilakos A, Anagnostakis K, Pedrycz W (2001) Application of Computational intelligence techniques in active networks. Soft Comput 5:264–271

    Article  MATH  Google Scholar 

  24. Walker R (2001) Parallel clustering system using the methodologies of evolutionary computations. In: Proceedings of CEC 2001. IEEE, Piscataway, pp 831–838

  25. Walker R (2002) Using nearest neighbors to discover Web page similarities. In: Arabnia H (ed) PDPTA’02: Proceedings of the 2002 international conference on parallel and distributed processing techniques and applications. CSREA Press, pp 157–163

  26. Walker R (2003) Tocorime Apicu: design of an experimental search engine using an information sharing model. Ph.D. Dissertation, University of California

  27. Walker R (2004) Search engine development using evolutionary computation methodologies. In: Tan K, Lim M, Yao X, Wang L (eds) Recent advances in simulated evolution and learning. World Scientific Singapore, pp 284–306

  28. Walker R (2005) Hierarchical task topology for retrieving information from within a simulated information ecosystem. J Netw Comput Appli 28:77–96

    Article  Google Scholar 

  29. Yahoo (2003) Yahoo! news—front page. Yahoo Inc, Santa Clara

    Google Scholar 

  30. Yuwono B, Lam S, Ying J, Lee D (1996) A world wide web resource discovery system. Worldw Web J 1(1):145–158

    Google Scholar 

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Authors and Affiliations

  1. Tapicu, Inc., P.O. Box 88492, Los Angeles, CA, 90009, USA

    Reginald L. Walker

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  1. Reginald L. Walker
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Walker, R.L. Purposive behavior of honeybees as the basis of an experimental search engine. Soft Comput 11, 697–716 (2007). https://doi.org/10.1007/s00500-006-0114-2

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