Belle, Vaishak. <br/><br/>
Toward Robots That Reason: Logic, Probability & Causal Laws  [electronic resource] / 
by Vaishak Belle. 
 - 1st ed. 2023. 
 - XIII, 190 p. 27 illus., 14 illus. in color.  online resource. 
 - Synthesis Lectures on Artificial Intelligence and Machine Learning,  1939-4616 .
 - Synthesis Lectures on Artificial Intelligence and Machine Learning, .
<br/><br/>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. 
<br/><br/> 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. . 
<br/><br/><label>ISBN: </label>9783031210037 
<br/><br/><label>Standard No.: </label>10.1007/978-3-031-21003-7  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Artificial intelligence.<br/>Robotics.<br/>Computer science--Mathematics.<br/>Mathematical statistics.<br/>Logic design.<br/>Application software.<br/>Data mining.<br/>Artificial Intelligence.<br/>Robotics.<br/>Probability and Statistics in Computer Science.<br/>Logic Design.<br/>Computer and Information Systems Applications.<br/>Data Mining and Knowledge Discovery.
<br/><br/><label>LC Class. No.: </label>Q334-342 TA347.A78 
<br/><br/><label>Dewey Class. No.: </label>006.3