by Steven M. LaValle
Publisher: Cambridge University Press 2006
Number of pages: 842
Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.
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by Herbert Edelsbrunner - Duke University
The main topics to be covered in this course are: Design Techniques; Searching; Prioritizing; Graph Algorithms; Topological Algorithms; Geometric Algorithms; NP-completeness. The emphasis will be on algorithm design and on algorithm analysis.
by Luc Devroye - Birkhauser
In these lecture notes, we attempt to explain the connection between the expected time of various bucket algorithms and the distribution of the data. The results are illustrated on standard searching, sorting and selection problems.
by Allen B. Downey - Green Tea Press
This book is intended for college students in computer science and related fields. The book also presents basic aspects of software engineering practice, including version control and unit testing. Each chapter ends with an exercises.
by Guy Blelloch - The MIT Press
Vector Models for Data-Parallel Computing describes a model of parallelism that extends and formalizes the Data-Parallel model on which the Connection Machine and other supercomputers are based. It presents many algorithms based on the model.