Publisher's Synopsis
Computer science is not so much about the computer as a specific piece of technology as it is about the more general phenomenon of computation itself, the design of processes that represent and manipulate information. Such processes turn out to obey their own inherent laws, and they are performed not only by computers but by people, by organizations, and by systems that arise in nature. We refer to these computational processes as algorithms. Designing the right algorithm for a given application is a difficult job. It requires a major creative act, taking a problem and pulling a solution out of the ether. This is much more difficult than taking someone else's idea and modifying it or tweaking it to make it a little better. The space of choices you can make in algorithm design is enormous, enough to leave you plenty of freedom to hang yourself. This view of algorithms is general enough to capture both the way a computer processes data and the way a person performs calculations by hand. For example, the rules for adding and multiplying numbers that we learn as children are algorithms; the rules used by an airline company for scheduling flights constitute an algorithm; and the rules used by a search engine like Google for ranking Web pages constitute an algorithm. It is also fair to say that the rules used by the human brain to identify objects in the visual field constitute a kind of algorithm, though we are currently a long way from understanding what this algorithm looks like or how it is implemented on our neural hardware. The need for efficient algorithms arises in nearly every area of computer science. But the type of problem to be solved, the notion of what algorithms are "efficient," and even the model of computation can vary widely from area to area. This book presents advances in the research and applications of algorithms. There is a rich history of theoretical research and practical solutions in this field. Algorithms have proved to be successful in a variety of problem domains in science, engineering and business. This real world motivation for studying algorithmic design methods has led not only to the development of many software packages but also to some beautiful mathematics which has no direct application to applied problems. This book highlights a few of the exciting recent developments in design of algorithms. Computer science is not so much about the computer as a specific piece of technology as it is about the more general phenomenon of computation itself, the design of processes that represent and manipulate information. Such processes turn out to obey their own inherent laws, and they are performed not only by computers but by people, by organizations, and by systems that arise in nature. We refer to these computational processes as algorithms. Designing the right algorithm for a given application is a difficult job. It requires a major creative act, taking a problem and pulling a solution out of the ether. This is much more difficult than taking someone else's idea and modifying it or tweaking it to make it a little better. The space of choices you can make in algorithm design is enormous, enough to leave you plenty of freedom to hang yourself. This view of algorithms is general enough to capture both the way a computer processes data and the way a person performs calculations by hand. For example, the rules for adding and multiplying numbers that we learn as children are algorithms; the rules used by an airline company for scheduling flights constitute an algorithm; and the rules used by a search engine like Google for ranking Web pages constitute an algorithm. It is also fair to say that the rules used by the human brain to identify objects in the visual field constitute a kind of algorithm, though we are currently a long way from understanding what this algorithm looks like or how it is implemented on our neural hardware. The need for efficient algorithms arises in nearly every area of computer science. But the type of problem to be solved, the notion of what algorithms are "efficient," and even the model of computation can vary widely from area to area. This book presents advances in the research and applications of algorithms. There is a rich history of theoretical research and practical solutions in this field. Algorithms have proved to be successful in a variety of problem domains in science, engineering and business. This real world motivation for studying algorithmic design methods has led not only to the development of many software packages but also to some beautiful mathematics which has no direct application to applied problems. This book highlights a few of the exciting recent developments in design of algorithms. Computer science is not so much about the computer as a specific piece of technology as it is about the more general phenomenon of computation itself, the design of processes that represent and manipulate information. Such processes turn out to obey their own inherent laws, and they are performed not only by computers but by people, by organizations, and by systems that arise in nature. We refer to these computational processes as algorithms. Designing the right algorithm for a given application is a difficult job. It requires a major creative act, taking a problem and pulling a solution out of the ether. This is much more difficult than taking someone else's idea and modifying it or tweaking it to make it a little better. The space of choices you can make in algorithm design is enormous, enough to leave you plenty of freedom to hang yourself. This view of algorithms is general enough to capture both the way a computer processes data and the way a person performs calculations by hand. For example, the rules for adding and multiplying numbers that we learn as children are algorithms; the rules used by an airline company for scheduling flights constitute an algorithm; and the rules used by a search engine like Google for ranking Web pages constitute an algorithm. It is also fair to say that the rules used by the human brain to identify objects in the visual field constitute a kind of algorithm, though we are currently a long way from understanding what this algorithm looks like or how it is implemented on our neural hardware. The need for efficient algorithms arises in nearly every area of computer science. But the type of problem to be solved, the notion of what algorithms are "efficient," and even the model of computation can vary widely from area to area. This book presents advances in the research and applications of algorithms. There is a rich history of theoretical research and practical solutions in this field. Algorithms have proved to be successful in a variety of problem domains in science, engineering and business. This real world motivation for studying algorithmic design methods has led not only to the development of many software packages but also to some beautiful mathematics which has no direct application to applied problems. This book highlights a few of the exciting recent developments in design of algorithms.
