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- W2157899911 abstract "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." @default.
- W2157899911 created "2016-06-24" @default.
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- W2157899911 date "2004-09-01" @default.
- W2157899911 modified "2023-09-27" @default.
- W2157899911 title "A MATHEMATICAL FRAMEWORK FOR CELLULAR LEARNING AUTOMATA" @default.
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- W2157899911 doi "https://doi.org/10.1142/s0219525904000202" @default.
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