Resource-Competing Oscillator Network as a Model of Amoeba-Based Neurocomputer

  • Authors:

  • Masashi Aono;Yoshito Hirata;Masahiko Hara;Kazuyuki Aihara

  • Affiliations:

  • Flucto-Order Functions Asian Collaboration Team, Advanced Science Institute, RIKEN, Wako, Japan 351-0198;Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan 153-8505;Flucto-Order Functions Asian Collaboration Team, Advanced Science Institute, RIKEN, Wako, Japan 351-0198;Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan 153-8505 and ERATO Aihara Complexity Modelling Project, JST, Shibuya-ku, Tokyo, Japan 151-0064

  • Venue:
  • UC '09 Proceedings of the 8th International Conference on Unconventional Computation
  • Year:
  • 2009

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Abstract

An amoeboid organism, Physarum , exhibits rich spatiotemporal oscillatory behavior and various computational capabilities. Previously, the authors created a recurrent neurocomputer incorporating the amoeba as a computing substrate to solve optimization problems. In this paper, considering the amoeba to be a network of oscillators coupled such that they compete for constant amounts of resources, we present a model of the amoeba-based neurocomputer. The model generates a number of oscillation modes and produces not only simple behavior to stabilize a single mode but also complex behavior to spontaneously switch among different modes, which reproduces well the experimentally observed behavior of the amoeba. To explore the significance of the complex behavior, we set a test problem used to compare computational performances of the oscillation modes. The problem is a kind of optimization problem of how to allocate a limited amount of resource to oscillators such that conflicts among them can be minimized. We show that the complex behavior enables to attain a wider variety of solutions to the problem and produces better performances compared with the simple behavior.