English, Article edition: A MATHEMATICAL FRAMEWORK FOR CELLULAR LEARNING AUTOMATA HAMID BEIGY; M. R. MEYBODI

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Bookmark: http://trove.nla.gov.au/version/143581
Physical Description
  • article
Language
  • English

Edition details

Title
  • A MATHEMATICAL FRAMEWORK FOR CELLULAR LEARNING AUTOMATA
Author
  • HAMID BEIGY
  • M. R. MEYBODI
Physical Description
  • article
Notes
  • The cellular learning automata, which is a combination of cellular automata, and learning automata, is a new recently introduced model. This model is superior to cellular automata because of its ability to learn and is also superior to a single learning automaton because it is a collection of learning automata which can interact with each other. The basic idea of cellular learning automata, which is a subclass of stochastic cellular learning automata, is to use the learning automata to adjust the state transition probability of stochastic cellular automata. In this paper, we first provide a mathematical framework for cellular learning automata and then study its convergence behavior. It is shown that for a class of rules, called commutative rules, the cellular learning automata converges to a stable and compatible configuration. The numerical results also confirm the theoretical investigations.
  • Cellular learning automata, cellular automata, learning automata, interconnected automata
  • RePEc:wsi:acsxxx:v:07:y:2004:i:03:p:295-319
Language
  • English
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