Handbook of Knowledge Representation
by Frank van Harmelen, Vladimir Lifschitz, Bruce Porter
Publisher: Elsevier Science 2008
Number of pages: 1035
Knowledge Representation, which lies at the core of Artificial Intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically. The Handbook of Knowledge Representation is an up-to-date review of twenty-five key topics in knowledge representation, written by the leaders of each field. This book is an essential resource for students, researchers and practitioners in all areas of Artificial Intelligence.
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by Victor Eijkhout - University of Texas
A computational scientist needs knowledge of several aspects of numerical analysis and discrete mathematics. This text covers: computer architecture, parallel computers, machine arithmetic, numerical linear algebra, applications.
by Robert M. Keller - Harvey Mudd College
This book is intended for a second course in computer science, one emphasizing principles wherever it seems possible. It is not limited to programming, it attempts to use various programming models to explicate principles of computational systems.
by Peter Van Roy, Seif Haridi - The MIT Press
Covered topics: concurrency, state, distributed programming, constraint programming, formal semantics, declarative concurrency, message-passing concurrency, forms of data abstraction, building GUIs, transparency approach to distributed programming.
by David S. Touretzky - Benjamin-Cummings Pub Co
This is a gentle introduction to Common Lisp for students taking their first programming course. No prior mathematical background beyond arithmetic is assumed. There are lots of examples, the author avoided technical jargon.