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Toward Robots That Reason: Logic, Probability & Causal Laws-电子书百科大全

Toward Robots That Reason: Logic, Probability & Causal Laws

Toward Robots That Reason: Logic, Probability & Causal Laws (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Author: by Vaishak Belle (Author)
Publisher: Springer
Edition: 1st ed. 2023
Publication Date: 2023-02-21
Language: English
Print Length: 203 pages
ISBN-10: 3031210026
ISBN-13: 9783031210020

Book Description
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.

From the Back Cover

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.

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.

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