On expediency of Closed Asynchronous Dynamic Cellular Learning Automata

Abstract

Closed Asynchronous Dynamic Cellular Learning Automata (CADCLAs) have been reported recently. CADCLAs are hybrid models based on Cellular Automata (CAs) and Learning Automata (LAs). Because of distributed computation characteristic of CAs and probabilistic decision making nature of LAs, analyzing the performance of CADCLA based algorithms is difficult. The expediency metric has been used to study the performance of the LA based models. With respect to this metric, the performance of CADCLAs have not been studied in the literature. In this paper, we suggest sufficient conditions under them a CADCLA is expedient.