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Nanorobotic Agents Communication Using Bee-Inspired Swarm Intelligence
Computer Science Department, University of Botswana, Gaborone, Botswana
Computer Science Department, University of Botswana, Gaborone, Botswana
- 1 Computer Science Department, University of Botswana, Gaborone, Botswana
- 2 Computer Science Department, University of Botswana, Gaborone, Botswana
Wireless Sensor Network·Volume 05 (2013)·Pages 208–214·Published 15 October 2013·DOI10.4236/wsn.2013.510024
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Abstract
The main goal of this paper is to design nanorobotic agent communication mechanisms which would yield coordinated swarm behavior. Precisely we propose a bee - inspired swarm control algorithm that allows nanorobotic agents commu nication in order to converge at a specific target. In this paper, we present experiment to test convergence speed and quality in a simulated multi - agent deployment in an environment with a single target. This is done to measure whether the use of our algorithm or random guess improves efficiency in terms of convergence and quality. The results attained from the experiments indicated that the use of our algorithm enhance the coordinated movement of agents towards the target compared to random guess.
KeywordsNanorobotsAgentsNanitesSwarmsNanotechnologyBeelike Nano-Machine
- A. Cavalcanti and R. A. Freitsa, Jr., “Nanorobotics Control Design: A Collective Behaviour for Approach for Medicine,” IEEE Transactions on Nanobioscience, Vol. 4, No. 2, 2005, pp. 134-139.
- A. Cavalcanti, R. A. Freitsa Jr. and L. C. Krety, “Nanorobotics Control Design: A Practical Aproach Tutorial,” ASME Press, Salt Lake City, 2004.
- R. A. Freitas Jr., “Current Status of Nanomedicine and Medical Nanorobotics,” Computational and Theoretical Nanoscience, Vol. 2, No. 1, 2005, pp. 1-25.
- A. Galstyan and T. Hogg, “Kristina Lerman Modelling and Mathematical Analysis of Swarms of Microscopic Robots,” Pasadena, 2006, pp. 201-208.
- T. E. Izquierdo, “Collective Intelligence in Multi Agent Robotics: Stigmery, Self Organisation and Evolution,” University of Sucssex Press, UK, 2004.
- C. W. Raynolds, “Flocks, Heads and Schools: A Distributed Behavioural Model,” Computer Graphics, Vol. 21, No. 4, 1987, pp. 25-34.
- C. Chibaya and S. Bangay, “A Probabilistic Movement Model for Shortest Path Formation in Virtual Ant like Agents,” Proceedings of the 2007 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists on IT Research in Developing Countries, South Africa, 2007, pp. 9-18.
- N. Pavol, “Bee Hive Metaphor for Web Search,” Communication and Cognition-Artificial Intelligence, Vol. 23, No. 1-4, 2006, pp. 15-20.
- G. Beni and J. Wang, “Swarm Intelligence in Cellular Systems,” Proceedings of NATO Advanced Workshop on Robots and Biological Systems, Tuscany, 26-30 June 1989.
- D. M. Gordon, “The Organisation of Work in Social Insect Colonies,” Nature, Nature Publishing Group, Vol. 380, No. 6570, 1996, pp. 121-124.
- R. A. Freitas Jr., “Current Status of Nanomedicine and Medical Nanorobotics,” American Scientific Publisher, USA, 2005.
- J. R. Krebs and D. W. Stephen, “Foraging Theory,” Monographs in Behavior and Ecology, Princeton University Press, Princeton, 1986.
- K. V. Frisch, “The Dancing Bees: Their Vision, Chemical Senses and Language,” Cornell University Press, Ithaca, 1956, pp. 36-39.
- Lammens, S. Dejong, K. Tuyls, A. Nowe, et al., “Bee Behaviour in Multi-Agent Systems: A Bee Foraging Algorithm,” Proceedings of the 7th ALAMAS Symposium, Maastricht, 2007.
- D. Teodorovic, “Swarm Intelligence Systems for Transportation Engineering: Principles and Applications,” Elsevier, Vol. 16, No. 6, 2008, pp. 651-667.