The first part of this preface is for the student; the second for the instructor. But whoever you are, welcome to both parts. For the Student You have finished secondary school, and are about to begin at a university or technical college. You want to study computing. The course includes some mathematics { and that was not necessarily your favourite subject. But there is no escape: some finite mathematics is a required part of the first year curriculum. That is where this book comes in. Its purpose is to provide the basics { the essentials that you need to know to understand the mathematical language that is used in computer and information science. It does not contain all the mathematics that you will need to look at through the several years of your undergraduate career. There are other very good, massive volumes that do that. At some stage you will probably find it useful to get one and keep it on your shelf for reference. But experience has convinced this author that no matter how good the compendia are, beginning students tend to feel intimidated, lost, and unclear about what parts to focus on. This short book, on the other hand, offers just the basics which you need to know from the beginning, and on which you can build further when needed.
Inhaltsverzeichnis
Collecting Things Together: Sets.- Comparing Things: Relations.- Associating One Item with Another: Functions.- Recycling Outputs as Inputs: Induction and Recursion.- Counting Things: Combinatorics.- Weighing the Odds: Probability.- Squirrel Math: Trees.- Yea and Nay: Propositional Logic.- Something about Everything: Quantificational Logic.
Über den Autor
David Makinson is currently Visiting Professor at London School of Economics (LSE). Previous affiliations include the Department of Computer Science at King’s College London, UNESCO in Paris, and the American University of Beirut in Lebanon. He is well known for his early research in modal and deontic logics, and more recently in the logic of belief change (as one of the founders of the AGM paradigm) and nonmonotonic reasoning.
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