Overview
- Explains the need for integrating logic and probability in AI systems and the challenges that arise in doing so
- Presents a model for capturing causal laws that describe dynamics and computational reasoning ideas
- Includes both high-level ideas and detailed exercises that employ technical applications
Part of the book series: Synthesis Lectures on Artificial Intelligence and Machine Learning (SLAIML)
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About this book
This book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge.
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Keywords
Table of contents (11 chapters)
Authors and Affiliations
About the author
Vaishak Belle, Ph.D., is a Chancellor’s Fellow and Reader at The University of Edinburgh School of Informatics. He is also an Alan Turing Institute Faculty Fellow, a Royal Society University Research Fellow, and a member of the Royal Society of Edinburgh’s Young Academy of Scotland. Dr. Belle directs a research lab on artificial intelligence at The University of Edinburgh, specializing in the unification of symbolic logic and machine learning. He has co-authored over 50 scientific articles on AI, and has won several best paper awards.
Bibliographic Information
Book Title: Toward Robots That Reason: Logic, Probability & Causal Laws
Authors: Vaishak Belle
Series Title: Synthesis Lectures on Artificial Intelligence and Machine Learning
DOI: https://doi.org/10.1007/978-3-031-21003-7
Publisher: Springer Cham
eBook Packages: Synthesis Collection of Technology (R0), eBColl Synthesis Collection 12
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-21002-0Published: 21 February 2023
Softcover ISBN: 978-3-031-21005-1Published: 22 February 2024
eBook ISBN: 978-3-031-21003-7Published: 20 February 2023
Series ISSN: 1939-4608
Series E-ISSN: 1939-4616
Edition Number: 1
Number of Pages: XIII, 190
Number of Illustrations: 13 b/w illustrations, 14 illustrations in colour
Topics: Artificial Intelligence, Robotics, Probability and Statistics in Computer Science, Logic Design, Computer Applications, Data Mining and Knowledge Discovery