history, evolution of civilizations, pattern recognition


The Pattern Recognition algorithm in Artificial Intelligence has been applied to many fields and proven to be very effective when seeking out patterns that arise from huge amount of raw data. As world history has evolved, it has revealed the shift of hegemony from one civilization to another, for example, from the Spanish Empire to the Kingdom of France, from the Kingdom of France to the British Empire, and from the British Empire to the United States. As historians have shown, the relevant eras are the Spanish Golden Age, the Age of Enlightenment, Pax Britannica, and Pax Americana. Since the data about these eras are too huge to collect, I believe one can manually find out useful patterns by critically thinking about similarities in history. I propose a solution of finding each era’s beginning and ending year, then quartering years, along with similar but critical events which happen in these years. By applying this method, one can observe the evolution of history step-by-step and can extract the pure logic behind it.