Social cohesion and optimal development outcomes: A study through graph theory, Markov Chain and Artificial Intelligence

Abstract

Lack of cohesion among human beings is a major problem in modern India. This absence of cohesion appeared due to many historical, geographical and economic factors. It has ultimately culminated in differentiated development outcomes in India. This work wants to evaluate the effect of social cohesion on the development achievements. To that respect Graph theory, Markov chain analysis and Artificial Intelligence have been used. Here society has been conceived as a network of n agents. To initiate the Markov process the idea of Genetic Algorithm is used. On the other hand this work tries to measure the Cohesion Density Index for the concerned network and correlation with the time and apace complexity of that very network. This work actually compares the stationary states through Artificial Intelligence to find the most acceptable or optimum. It is concluded that the level of cohesion among different social groups can largely influence the expected outcome of any inclusionary development programme. This lack of cohesiveness within the Indian society due to some strong religio-philosophical reasons is one of the greatest challenges to India in achieving desired inclusive growth. In this paper it is shown that increasing the connectedness of the society can improve the efficiency of the development programs.