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Cellular learning automata with external input and its applications in pattern recognition

Ahangaran, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/ICSCCW.2009.5379465
  3. Abstract:
  4. Cellular learning automata (CLA) which has been introduced recently, is a combination of cellular automata (CA) and learning automata (LA). A CLA is a CA in which a LA is assigned to its every cell. The LA residing in each cell determines the state of the cell on basis of its action probability vector. Like CA, there is a local rule that CLA operates under it. In this paper we introduce a new model of CLA in which each cell gets an external input vector from the environment in addition to reinforcement signal, so this model can work in non-stationary environments. Then two applications of the new model on image segmentation and clustering are given, and the results show that the proposed algorithm outperforms the similar algorithms. ©2009 IEEE
  5. Keywords:
  6. Cellular learning automata ; External input ; External input vector ; Learning Automata ; Local rules ; New model ; Non-stationary environment ; Probability vector ; Reinforcement signal ; Algorithms ; Cellular automata ; Image segmentation ; Pattern recognition systems ; Reinforcement ; Robots ; Soft computing ; Systems analysis ; Translation (languages) ; Automata theory
  7. Source: ICSCCW 2009 - 5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control ; 2009 ; 9781424434282 (ISBN)
  8. URL: http://ieeexplore.ieee.org/document/5379465/?reload=true