Editors:
- There is no up-to-date book which covers this topic area, only a few scattered research/conference papers which address this topic
- Chapters writen by International leaders from both industry and academia working in this field
- Discusses Transport Visualisation tool for PDDL Planning
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (14 chapters)
-
Front Matter
-
Knowledge Capture and Encoding
-
Front Matter
-
-
Interaction, Visualisation, and Explanation
-
Front Matter
-
About this book
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 booktargets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.
Editors and Affiliations
-
Department of Computer Science, University of Huddersfield, Huddersfield, UK
Mauro Vallati, Diane Kitchin
About the editors
Dr Mauro Vallati is a Senior Lecturer in the Department of Computer Science at the University of Huddersfield. He has extensive experience in real-world applications of AI methods and techniques, with his research focusing on the Knowledge Engineering aspects of AI applications. Among the others, he investigated the useof AI for managing urban traffic control, for controlling robots, and for reducing the energy consumption of manufacturing machine tools. Dr. Vallati has published a significant number of papers in top AI venues, and has co-organised important events for the AI field, such as workshops, competitions, and conferences. He delivered numerous tutorials in important AI venues.
Bibliographic Information
Book Title: Knowledge Engineering Tools and Techniques for AI Planning
Editors: Mauro Vallati, Diane Kitchin
DOI: https://doi.org/10.1007/978-3-030-38561-3
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-38560-6Published: 26 March 2020
Softcover ISBN: 978-3-030-38563-7Published: 26 March 2021
eBook ISBN: 978-3-030-38561-3Published: 25 March 2020
Edition Number: 1
Number of Pages: VIII, 277
Number of Illustrations: 44 b/w illustrations, 53 illustrations in colour
Topics: Knowledge based Systems, Knowledge Management, Data Mining and Knowledge Discovery