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By Tshilidzi Marwala

Causality has been a subject matter of research for a very long time. usually causality is stressed with correlation. Human instinct has developed such that it has realized to spot causality via correlation. during this ebook, 4 major subject matters are thought of and those are causality, correlation, synthetic intelligence and selection making. A correlation laptop is outlined and outfitted utilizing multi-layer perceptron community, imperative part research, Gaussian combination types, genetic algorithms, expectation maximization approach, simulated annealing and particle swarm optimization. additionally, a causal computer is outlined and equipped utilizing multi-layer perceptron, radial foundation functionality, Bayesian information and Hybrid Monte Carlo equipment. either those machines are used to construct a Granger non-linear causality version. moreover, the Neyman–Rubin, Pearl and Granger causal versions are studied and are unified. the automated relevance selection is usually utilized to increase Granger causality framework to the non-linear area. the idea that of rational determination making is studied, and the speculation of flexibly-bounded rationality is used to increase the idea of bounded rationality in the precept of the indivisibility of rationality. the idea of the marginalization of irrationality for determination making can be brought to accommodate satisficing inside of irrational stipulations. The tools proposed are utilized in biomedical engineering, tracking and for modelling interstate conflict.

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Causality, Correlation and Artificial Intelligence for Rational Decision Making by Tshilidzi Marwala

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