Multistate network model for the pathfinding problem with a self-recovery property

Kei Ichi Ueda, Masaaki Yadome, Yasumasa Nishiura

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In this study, we propose a continuous model for a pathfinding system. We consider acyclic graphs whose vertices are connected by unidirectional edges. The proposed model autonomously finds a path connecting two specified vertices, and the path is represented by a stable solution of the proposed model. The system has a self-recovery property, i.e., the system can find a path when one of the connections in the existing path is suddenly terminated. Further, we demonstrate that the appropriate installation of inhibitory interaction improves the search time.

Original languageEnglish
Pages (from-to)32-38
Number of pages7
JournalNeural Networks
Publication statusPublished - 2015 Feb 1


  • Attractors
  • Dynamical systems
  • Pathfinding

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Artificial Intelligence


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