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Cellular learning automata with multiple learning automata in each cell and its applications

Beigy, H ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/TSMCB.2009.2030786
  3. Publisher: 2010
  4. Abstract:
  5. The cellular learning automaton (CLA), which is a combintion of cellular automaton (CA) and learning automaton (LA), is introduced recently. This model is superior to CA because of its ability to learn and is also superior to single LA because it is a collection of LAs which can interact with each other. The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. Recently, various types of CLA such as synchronous, asynchronous, and open CLAs have been introduced. In some applications such as cellular networks, we need to have a model of CLA for which multiple LAs reside in each cell. In this paper, we study a CLA model for which each cell has several LAs. It is shown that, for a class of rules called commutative rules, the CLA model converges to a stable and compatible configuration. Two applications of this new model such as channel assignment in cellular mobile networks and function optimization are also given. For both applications, it has been shown through computer simulations that CLA-based solutions produce better results
  6. Keywords:
  7. Cellular learning automaton (CLA) ; Dynamic channel assignment (DCA) ; Learning automaton (LA) ; Basic idea ; Cellular learning automata ; Cellular mobile networks ; Cellular network ; Channel Assignment ; Dynamic channel assignment ; Function Optimization ; Learning Automata ; Learning automaton ; New model ; State transition probabilities ; Cellular automata ; Cellular neural networks ; Channel capacity ; Computer simulation ; Pattern recognition systems ; Robots ; Translation (languages) ; Automata theory
  8. Source: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics ; Volume 40, Issue 1 , 2010 , Pages 54-65 ; 10834419 (ISSN)
  9. URL: http://ieeexplore.ieee.org/document/5306498