Evolutionary game theory to predict the population growth in Few districts of Tamil Nadu and Kerala

• Published in: Measurement. Sensors Vol. 27; p. 100736
• Main Authors: N, Kalaivani, Visalakshidevi, E. Mona
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2023; Elsevier
• Subjects: Deterministic game theory; Evolutionary game theory; Game theory; Mathematics subject classification; Tamil Nadu and Kerala; Deterministic game theory; Mathematics subject classification; Game theory; Tamil Nadu and Kerala; Evolutionary game theory
• ISSN: 2665-9174; 2665-9174
• DOI: 10.1016/j.measen.2023.100736

The conventional models in Game Theory focuses entirely on the relative fitness of the population agents leaving the dynamic behaviour of the size of population left uncovered. Therefore, a robust model is required to combine both the growth dynamics and internal evolution of agents. Evolutionary Game Theory to Predict the Population Growth in Few Districts of Tamil Nadu and Kerala. In this paper, we develop an Evolutionary Game Theory (EGT) model which is integrated with the Residual deterministic learning (RDL) model to increase the rate of prediction of the population growth. Various deterministic models including Arithmetic Increase, Geometric Increase, Incremental Increase and Simple graphical models are used to improve the prediction ability of EGT. The EGT combined with RDL forms REGT model that is found scalable to predict the long-term population growth in near proximal districts of Tamil Nadu and Kerala. Various inputs affecting the population growth are considered as the inputs to the REGT model to the Matlab simulator. The experimentation shows that the proposed REGT model is better in predicting the population growth than the existing game theory models.