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020 _a9789332543515
040 _cNational Institute of Technology Goa
082 _a006.3
_bRUS/NOR
100 _aRussell, Stuart J
110 _aNorvig, Peter
245 0 _aArtificial intelligence: a modern approach
250 _a3rd
260 _aNoida:
_b Pearson,
_c 2019
300 _a1146p.: 18x24x2; Paperback
520 _aAbout the book: There have been important applications of AI technology, such as the widespread deployment of practical speech recognition, machine translation, autonomous vehicles, and household robotics. There have been algorithmic landmarks, such as the solution of the game of checkers. There has also been a great deal of theoretical progress, particularly in areas such as probabilistic reasoning, machine learning, and computer vision. Features • Nontechnical learning material provides a simple overview of major concepts • Expanded coverage of topics such as constraint satisfaction, local search planning methods, multi-agent systems, game theory, statistical natural language processing and uncertain reasoning over time • More detailed descriptions of algorithms for probabilistic inference, fast propositional inference, probabilistic learning approaches including EM, and other topics • Updated and expanded exercises • A unified, agent-based approach to AI : Organizes the material around the task of building intelligent agents • Comprehensive, up-to-date coverage : Includes a unified view of the field organized around the rational decision making paradigm • In-depth coverage of basic and advanced topics which provides students with a basic understanding of the frontiers of AI without compromising complexity and depth. • Pseudo-code versions of the major AI algorithms are presented in a uniform fashion, and Actual Common Lisp and Python implementations of the presented algorithms are available via the Internet
650 _aComputer Sciebce Engineering; Intelligent agents; Adversarial search; Probabilistic reasoning; Reinforcement learning; Natural language processing; Robotics; Philosophical foundations
942 _cBK
_2ddc
_n0
999 _c4277
_d4277