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Autonomous robots based on inspiration from biology

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References

  • Amari, S. -I., Arbib, M. A., and Kötter, R. (2003) Introduction to the 2003 special issue on neuroinformatics. Neural Netw. 16, 1235–1236.

    Article  Google Scholar 

  • Arbib, M. A. (1982) Rana computatrix: An evolving model of visuo-motor co-ordination in frog and toad. In: Machine Intelligence 10. Hayes, J. E., Michie, D., and Pao, Y. H. (eds.) Ellis Horwood Publishers, Chichester, pp. 501–517.

    Google Scholar 

  • Arbib, M. A. (2003) Rana computatrix to human language: towards a computational neuroethology of language evolution. Phil. Trans. R. Soc. Lond. A 361, 2345–2379.

    Article  Google Scholar 

  • Arbib, M. A., Tinroongroj, N., and Plangprasopchok, A. The Brain Operation Database (BODB): from data and models to Brain Operating Principles and back again (in preparation).

  • Beer, R. D. (1990) Intelligence as Adaptive Behavior: An Experiment in Computational Neuroethology. Academic Press, New York.

    Google Scholar 

  • Beer, R. D., Ritzmann, R., and McKenna, T. M. (eds.) (1992) Biological Neural Networks in Invertebrate Neuroethology and Robotics. Academic Press, New York.

    Google Scholar 

  • Braitenberg, V. (1965) Taxis, kinesis, decussation. Prog. Brain Res. 17, 210–222.

    Article  PubMed  CAS  Google Scholar 

  • Braitenberg, V. (1984) Vehicles: experiments in synthetic psychology. MIT Press, Cambridge, MA.

    Google Scholar 

  • Cliff, D. (1992) Neural networks for visual tracking in an artificial fly. In: Towards a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life (ECAL91). Varela, F. J. and Bourgine, P. (eds.) MIT Press Bradford Books, Cambridge, MA, pp. 78–87.

    Google Scholar 

  • Damper, R. I. (2003) Preface, Special issue on Biologically Inspired Robotics. Phil. Trans. R. Soc. Lond. A 361, 2081–2083.

    Article  Google Scholar 

  • Damper, R. I., French, R. L. B., and Scutt, T. W. (2000) ARBIB: An autonomous robot based on inspiration from biology. Robotics Autonomous Syst. 31, 247–274.

    Article  Google Scholar 

  • Guazzelli, G., Bota, B., and Arbib, M. A. (2001) Competitive Hebbian learning and the hippocampal place cell system: modeling the interaction of visual and path integration cues. Hippocampus 11, 216–239.

    Article  PubMed  CAS  Google Scholar 

  • Guazzelli, A., Corbacho, F. J., Bota, M., and Arbib, M. A. (1998) Affordances, motivation, and the world graph theory. Adaptive Behav. 6, 435–471.

    Article  Google Scholar 

  • House, D., (1989) Depth perception in frogs and toads: a study in neural computing. Lecture Notes in Biomathematics 80. Springer-Verlag, Berlin.

    Google Scholar 

  • Itti, L., Koch, C., and Niebur, E. (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20, 1254–1259.

    Article  Google Scholar 

  • Karniel, A., Fleming, K. M., Sanguineti, V., Alford, S., and Mussa-Ivaldi, F. A. (2002) Dynamic properties of the lamprey’s neuronal circuits as it drives a two-wheeled robot. In: Proceeding of the SAB’2002 Workshop on Motor Control in Humans and Robots.

  • Lettvin, J. Y., Maturana, H., McCulloch, W. S., and Pitts, W. H. (1959) What the frog’s eye tells the frog brain. Proc. IRE 47, 1940–1951.

    Article  Google Scholar 

  • Morris, R. (1984) Developments of a water-maze procedure for studying spatial learning in the rat. J. Neurosci. Methods 11, 47–60.

    Article  PubMed  CAS  Google Scholar 

  • Mussa-Ivaldi, A. and Miller, L.E. (2003) Brain-machine interfaces: computational demands and clinical needs meet basic neuroscience. Trends Neurosci. 28, 329–334.

    Article  CAS  Google Scholar 

  • Reger, B. D., Fleming, K. M., Sanguineti, V., Alford, S., and Mussa-Ivaldi, F. A. (2000) Connecting brains to robots: an artificial body for studying the computational properties of neural tissue. Artif. Life 6, 307–324

    Article  PubMed  CAS  Google Scholar 

  • Seth, A. K., Sporn, O., and Krichmar, J. L. (2005) Neurorobotic Models in Neuroscience and Neuroinformatics. Neuroinformatics 3:3, 167–170.

    Article  PubMed  Google Scholar 

  • Sutton, R. S. and Barto, A. G. (1998) Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA, USA.

    Google Scholar 

  • Walter, W. G. (1953) The living brain. Duckworth, London (Pelican edition, 1961, Penguin Books, Harmondsworth).

    Google Scholar 

  • Wiener, N. (1948) Cybernetics: or Control and Communication in the Animal and the Machine, The Technology Press and Wiley, 2nd edn. The MIT Press, Cambridge, MA, USA: p. 1961.

    Google Scholar 

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Authors and Affiliations

  1. Computer Science, Neuroscience, and the USC Brain Project, University of Southern California, 90089-2520, Los Angeles, CA, USA

    Michael A. Arbib

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  1. Michael A. Arbib
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Arbib, M.A. Autonomous robots based on inspiration from biology. Neuroinform 3, 281–286 (2005). https://doi.org/10.1385/NI:3:3:281

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