{"product_id":"artificial-intelligence-principles-and-practice","title":"Artificial Intelligence: Principles and Practice","description":"\u003cdiv data-cel-widget=\"bookDescription_feature_div\" data-csa-c-id=\"7y9w7h-rgk3d4-2xixgp-6jetc1\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-asin=\"0993745598\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-content-id=\"bookDescription\" data-csa-c-type=\"widget\" data-feature-name=\"bookDescription\" class=\"celwidget\" id=\"bookDescription_feature_div\"\u003e\n\u003cdiv class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\" data-a-expander-collapsed-height=\"280\" data-a-expander-name=\"book_description_expander\"\u003e\n\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content\" aria-expanded=\"false\"\u003e\n\u003cdiv id=\"bookDescription_feature_div\" class=\"celwidget\" data-feature-name=\"bookDescription\" data-csa-c-type=\"widget\" data-csa-c-content-id=\"bookDescription\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-asin=\"9819961939\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-id=\"ta5yoj-8ioql3-heksr8-7lupo6\" data-cel-widget=\"bookDescription_feature_div\"\u003e\n\u003cdiv data-a-expander-name=\"book_description_expander\" data-a-expander-collapsed-height=\"280\" class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\"\u003e\n\u003cdiv data-expanded=\"false\" class=\"a-expander-content a-expander-partial-collapse-content\"\u003e\n\u003cdiv data-cel-widget=\"bookDescription_feature_div\" data-csa-c-id=\"uabt8b-pqh18f-fjx0tp-chru34\" data-csa-c-is-in-initial-active-row=\"false\" data-csa-c-asin=\"1305110595\" data-csa-c-slot-id=\"bookDescription_feature_div\" data-csa-c-content-id=\"bookDescription\" data-csa-c-type=\"widget\" data-feature-name=\"bookDescription\" class=\"celwidget\" id=\"bookDescription_feature_div\"\u003e\n\u003cdiv class=\"a-expander-collapsed-height a-row a-expander-container a-spacing-base a-expander-partial-collapse-container\" data-a-expander-collapsed-height=\"280\" data-a-expander-name=\"book_description_expander\"\u003e\n\u003cdiv class=\"a-expander-content a-expander-partial-collapse-content\" data-expanded=\"false\"\u003e\n\u003cp\u003e\u003cspan\u003eThis book provides a complete introduction to Artificial Intelligence, covering foundational computational technologies, mathematical principles, philosophical considerations, and engineering disciplines essential for understanding AI. \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eArtificial Intelligence: Principles and Practice\u003c\/span\u003e\u003cspan\u003e emphasizes the interdisciplinary nature of AI, integrating insights from psychology, mathematics, neuroscience, and more. The book addresses limitations, ethical issues, and the future promise of AI, emphasizing the importance of ethical considerations in integrating AI into modern society. With a modular design, it offers flexibility for instructors and students to focus on specific components of AI, while also providing a holistic view of the field.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eTaking a comprehensive but concise perspective on the major elements of the field; from historical background to design practices, ethical issues and more, \u003c\/span\u003e\u003cspan class=\"a-text-italic\"\u003eArtificial Intelligence: Principles and Practice\u003c\/span\u003e\u003cspan\u003e provides the foundations needed for undergraduate or graduate-level courses. The important design paradigms and approaches to AI are explained in a clear, easy-to-understand manner so that readers will be able to master the algorithms, processes, and methods described.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eThe principal intellectual and ethical foundations for creating artificially intelligent artifacts are presented in Parts I and VIII. Part I offers the philosophical, mathematical, and engineering basis for our current AI practice. Part VIII presents ethical concerns for the development and use of AI. Part VIII also discusses fundamental limiting factors in the development of AI technology as well as hints at AI's promising future. We recommended that PART I be used to introduce the AI discipline and that Part VIII be discussed after the AI practice materials. Parts II through VII present the three main paradigms of current AI practice: the symbol-based, the neural network or connectionist, and the probabilistic.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eGenerous use of examples throughout helps illustrate the concepts, and separate end-of-chapter exercises are included. Teaching resources include a solutions manual for the exercises, PowerPoint presentation, and implementations for the algorithms in the book.\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003eTable of contents (28 chapters)\u003cbr\u003eFront Matter\u003cbr\u003ePages I-XVII\u003cbr\u003eI\u003cbr\u003eFront Matter\u003cbr\u003ePages 1-2\u003cbr\u003eThe Pre-History of Artificial Intelligence\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 3-25\u003cbr\u003eComputing, Representations, and Definitions of Artificial Intelligence\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 27-49\u003cbr\u003eII\u003cbr\u003eFront Matter\u003cbr\u003ePages 51-52\u003cbr\u003eThe State Space, Finite State Machines, and Artificial Life\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 53-72\u003cbr\u003eSearching the State Space\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 73-95\u003cbr\u003eHeuristic Search\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 97-123\u003cbr\u003eHeuristics: 2-Person Games and Theoretical Constraints\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 125-147\u003cbr\u003eIII\u003cbr\u003eFront Matter\u003cbr\u003ePages 149-150\u003cbr\u003eIntroduction to the Propositional and Predicate Calculi\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 151-170\u003cbr\u003eThe Predicate Calculus and Unification\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 171-190\u003cbr\u003eResolution: Reasoning with the Propositional and Predicate Calculi\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 191-220\u003cbr\u003eIV\u003cbr\u003eFront Matter\u003cbr\u003ePages 221-222\u003cbr\u003eThe Production System Representation and Search Engine\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 223-242\u003cbr\u003eAdvanced Applications of Symbol-Based AI: Planning and Learning\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 243-272\u003cbr\u003eUncertain Reasoning: Symbol Based\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 273-296\u003cbr\u003eV\u003cbr\u003eFront Matter\u003cbr\u003ePages 297-298\u003cbr\u003eIntroduction to Association-Based Knowledge Representations\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 299-319\u003cbr\u003eAssociation-Based Representations: Frames, Conceptual Graphs, WordNet, and FrameNet\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 321-339\u003cbr\u003eAn Introduction to Neural Networks\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 345-361\u003cbr\u003eThe Delta Rule, Backpropagation, and Matrix Representations\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 363-382\u003cbr\u003eDeep Learning: Introduction and Representations\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 383-408\u003cbr\u003eBuilding Language Models and Transformers\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 409-439\u003cbr\u003eAlternative Network Architectures: Prototypes and Classifiers\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 441-458\u003cbr\u003eAlternative Network Architectures: Attractor Networks and Memories\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 459-472\u003cbr\u003eVII\u003cbr\u003eFront Matter\u003cbr\u003ePages 473-474\u003cbr\u003eCounting, the Foundation for Probabilities\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 475-489\u003cbr\u003eBayes’ Theorem\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 491-506\u003cbr\u003eBayesian Belief Networks and Observable Markov Models\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 507-523\u003cbr\u003eHidden Markov and Alternative Probabilistic Models\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 525-546\u003cbr\u003eVIII\u003cbr\u003eFront Matter\u003cbr\u003ePages 547-549\u003cbr\u003eArtificial Intelligence: User’s Ethical Issues\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 551-572\u003cbr\u003eAI Ethical Issues: From a Social Perspective\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 573-599\u003cbr\u003eAI: Philosophical Perspectives, Current Limitations, and Future Promise\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages 601-614\u003cbr\u003eCorrection to: Artificial Intelligence: Principles and Practice\u003cbr\u003eGeorge F. Luger\u003cbr\u003ePages C1-C1\u003cbr\u003eBack Matter\u003cbr\u003ePages 615-638\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tableofcontents-section\" id=\"tableofcontents-section\"\u003e\n\u003cdiv class=\"page-section\"\u003e\n\u003cdiv class=\"section-content collapsed\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cb\u003eBOOKREAD™ 5-STEP SATISFACTION GUARANTEE\u003c\/b\u003e\u003c\/strong\u003e\u003cbr\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003e1. No Risk, 30-Day Money-Back Guarantee. \u003cbr\u003e2. instant download. 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