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Knowledge Engineering Tools and Techniques for AI Planning (Paperback, 1st ed. 2020): Mauro Vallati, Diane Kitchin Knowledge Engineering Tools and Techniques for AI Planning (Paperback, 1st ed. 2020)
Mauro Vallati, Diane Kitchin
R4,739 Discovery Miles 47 390 Ships in 10 - 15 working days

This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.

Knowledge Engineering Tools and Techniques for AI Planning (Hardcover, 1st ed. 2020): Mauro Vallati, Diane Kitchin Knowledge Engineering Tools and Techniques for AI Planning (Hardcover, 1st ed. 2020)
Mauro Vallati, Diane Kitchin
R4,770 Discovery Miles 47 700 Ships in 10 - 15 working days

This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.

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