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Ant-Based Computing

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Advances in Artificial Life (ECAL 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3630))

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Abstract

We propose a biologically and physically plausible model for ants and pheromones, and show this model to be sufficiently powerful to simulate the computation of arbitrary logic circuits. We thus establish that coherent deterministic and centralized computation can emerge from the collective behavior of simple distributed markovian processes as those followed by ants.

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References

  1. Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight, T.F., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous Computing. Communications of the Association for Computing Machinery 43(5) (2000)

    Google Scholar 

  2. Bonabeau, E., Theraulaz, G., Deneubourg, J.-L.: Fixed Response Thresholds and the Regulation of Division of Labour in Insect Societies. Bulletin of Mathematical Biology 60, 753–807 (1998)

    Article  MATH  Google Scholar 

  3. Deneubourg, J.-L., Aron, S., Goss, S., Pasteels, J.: The Self-Organising Exploratory Pattern of the Argentine Ant. Journal of Insect Behavior 3, 159–168 (1990)

    Article  Google Scholar 

  4. Deneubourg, J.-L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., Chrétien, L.: The Dynamics of Collective Sorting: Robot-Like Ants and Ant-Like Robots. In: Proceedings of the First International Conference on Simulation of Adaptive Behavior: From Animals to Animats (1991)

    Google Scholar 

  5. Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, U.S.A. (2004)

    Book  MATH  Google Scholar 

  6. Knight, T.F., Sussman, G.J.: Cellular Gate Technology. In: Proceedings of the First International Conference on Unconventional Models of Computation (1998)

    Google Scholar 

  7. Lumer, E., Faieta, B.: Diversity and Adaption in Populations of Clustering Ants. In: Proceedings of the Third International Conference on Simulation of Adaptive Behaviour: From Animals to Animats (1994)

    Google Scholar 

  8. Vestad, T., Marr, D.W.M., Munakata, T.: Flow Resistance for Microfluidic Logic Operations. Applied Physics Letters 84, 5074–5075 (2004)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Michael, L. (2005). Ant-Based Computing. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_58

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  • DOI: https://doi.org/10.1007/11553090_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28848-0

  • Online ISBN: 978-3-540-31816-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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