UID:
almafu_9961020785002883
Format:
1 online resource (201 pages) :
,
illustrations.
ISBN:
9783031210037
Series Statement:
Synthesis lectures on artificial intelligence and machine learning
Content:
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. .
Note:
Preface -- Acknowledgments -- Introduction -- Representation Matters -- From Predicate Calculus to the Situation Calculus -- Knowledge -- Probabilistic Beliefs -- Continuous Distributions -- Localization -- Regression & Progression -- Programs -- A Modal Reconstruction -- Conclusions.
Additional Edition:
Print version: Belle, Vaishak Toward Robots That Reason: Logic, Probability and Causal Laws Cham : Springer International Publishing AG,c2023 ISBN 9783031210020
Language:
English
DOI:
10.1007/978-3-031-21003-7
