Artificial Intelligence: Foundations of Computational Agents"Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents is a textbook aimed at junior to senior undergraduate students and first-year graduate students. It presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications. Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. It teaches the main principles and tools that will allow readers to explore and learn on their own. The text is supported by an online learning environment, AIspace, http://aispace.org, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving"--Provided by publisher. |
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able action agent algorithm allow answer assignment assume atom belief network building called carry chapter choose clause complexity conditional Consider consistent constraints controller cost decision defined definite depends derived determine distribution domain environment error example Exercise exists expected factor false Figure find first function give given goal graph individuals initial input intelligent interpretation knowledge base language learning logic means node object observed optimal ordering particular path planning position possible prediction preferences probability problem procedure proof properties proposition provides query question random reasoning relation represent representation resulting reward robot rule sample shows solution solve space specifies step strategy student Suppose symbols tion tree true utility variables