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Titlebook: Introduction to Artificial Intelligence; Wolfgang Ertel Textbook 2025Latest edition The Editor(s) (if applicable) and The Author(s), under

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發(fā)表于 2025-3-21 20:03:31 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Introduction to Artificial Intelligence
編輯Wolfgang Ertel
視頻videohttp://file.papertrans.cn/477/476472/476472.mp4
概述A concise, quick resource on A.I., excellent for courses and professional self-study.Presents an application-focused and hands-on approach to learning the subject.Provides study exercises, highlighted
叢書(shū)名稱(chēng)Undergraduate Topics in Computer Science
圖書(shū)封面Titlebook: Introduction to Artificial Intelligence;  Wolfgang Ertel Textbook 2025Latest edition The Editor(s) (if applicable) and The Author(s), under
描述.This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated .third. .edition .also includes new material on deep learning..Topics and features:.·??????? Presents an application-focused and hands-on approach to learning, with? ? ? ? ? supplementary teaching resources provided at an associated website?.·??????? Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification .(NEW).?.·??????? Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons?.·??????? Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art?.(NEW).?.·??????? Incl
出版日期Textbook 2025Latest edition
關(guān)鍵詞Artificial Intelligence; Agents; Logic; Search; Reasoning with Uncertainty; Machine Learning; Neural Netwo
版次3
doihttps://doi.org/10.1007/978-3-658-43102-0
isbn_softcover978-3-658-43101-3
isbn_ebook978-3-658-43102-0Series ISSN 1863-7310 Series E-ISSN 2197-1781
issn_series 1863-7310
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wies
The information of publication is updating

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1863-7310 o learning the subject.Provides study exercises, highlighted.This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and c
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Textbook 2025Latest editionsion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated .third. .
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,Logic Programming with?PROLOG,PROLOG, we invite the reader to solve some simple relational problems and puzzles. As a particular highlight, we introduce constraint logic programming, which enables us to elegantly solve for example non-trivial scheduling problems.
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,Reasoning with?Uncertainty,he powerful method of maximum entropy and Bayesian networks which are used in many applications. The medical diagnosis expert system L., developed by the author, is used to demonstrate the power of these formalisms.
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Neural Networks,iologists, psychologists, and doctors have tried to understand how the brain functions. Around 1900 came the revolutionary realization that these tiny physical building blocks of the brain, the nerve cells, and their connections, are responsible for awareness, associations, thoughts, consciousness, and the ability to learn.
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