The main assumption of this book is that if it requires a lot of time and effort to explain how something works, probably we do not understand it. Long explanations usually contain a lot of redundancy: repeated ideas, unused concepts, improperly defined relations, and so on. With a better understanding, normally after considerable research, we should be able to remove that redundancy. If we were able to come up with a perfect explanation about a research topic, that model must be a random string, otherwise it would contain redundant elements that can be removed, and so, either it is not random or it is not perfect.

The book is a comprehensive, self-contained, introduction to the Theory of Nescience, a new and powerful mathematical theory that has been developed with the aim of measuring how much we do not know, and discover new knowledge. The theory is based on the fact that randomness effectively imposes a limit on how much we can know about a particular research topic. Far from being a handicap, the proper understanding of this absolute epistemological limitation opens new opportunities in science and technology, both, to solve open problems, and to discover new knowledge. In the book it is also described some of the (surprisingly) large number of practical applications of this new theory, including artificial intelligence (data science, machine learning), the scientific method, computational creativity, software engineering, psychology, finance, biology and physics.

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