Titlebook: Artificial Intelligence; A Textbook Charu C. Aggarwal Textbook 2021 Springer Nature Switzerland AG 2021 Artificial Intelligence.Machine Lea

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書(shū)目名稱Artificial Intelligence影響因子(影響力)




書(shū)目名稱Artificial Intelligence影響因子(影響力)學(xué)科排名




書(shū)目名稱Artificial Intelligence網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Artificial Intelligence網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Artificial Intelligence被引頻次




書(shū)目名稱Artificial Intelligence被引頻次學(xué)科排名




書(shū)目名稱Artificial Intelligence年度引用




書(shū)目名稱Artificial Intelligence年度引用學(xué)科排名




書(shū)目名稱Artificial Intelligence讀者反饋




書(shū)目名稱Artificial Intelligence讀者反饋學(xué)科排名

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Propositional Logic,specific utility and cost functions can be used to play games like chess by searching for high-quality moves. The key point in search-oriented settings is that the domain knowledge is captured in the transition graph, starting/goal states, and in the utility functions associated with the nodes of th

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Machine Learning: The Inductive View,er to infer further conclusions. Unfortunately, this view of artificial intelligence is rather limited, since one cannot infer facts other than those that can be related to what is already present in the knowledge base, or can be enunciated as concrete sentences from these known facts. In the induct

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Domain-Specific Neural Architectures,computational units are layered and each unit in a particular layer is connected to a unit in the next layer. However, these types of architectures are not well suited to domain-specific settings, where there are known relationships among the attributes.

強(qiáng)化

Unsupervised Learning,pervised learning methods try to learn how the features are related to one another. In other words, unsupervised learning methods do not have a specific goal in mind in order to supervise the learning process. Rather, unsupervised methods learn the key patterns in the underlying data that relate all

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Reinforcement Learning,used to guide the learning process for future decisions. In other words, learning in intelligent beings is by reward-guided .. Almost all of biological intelligence, as we know it, originates in one form or other through an interactive process of trial and error with the environment. Since the goal

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Textbook 2021 methods:.?These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5..Inductive Learning Methods:.? These methods start with

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Concurrency and Multiversioning, data points and attributes to one another without a specific focus on any particular data items. In supervised learning, specific attributes (e.g., regressors or class labels) are more important, and therefore play the role of teachers (i.e., .) to the learning process.