Toward Robots That Reason: Logic, Probability & Causal Laws / Synthesis Lectures on Artificial Intelligence and Machine Learning (PDF)
(Sprache: Englisch)
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...
sofort als Download lieferbar
eBook (pdf)
43.99 €
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Toward Robots That Reason: Logic, Probability & Causal Laws / Synthesis Lectures on Artificial Intelligence and Machine Learning (PDF)“
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.
Autoren-Porträt von Vaishak Belle
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.
Bibliographische Angaben
- Autor: Vaishak Belle
- 2023, 2023, 190 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3031210034
- ISBN-13: 9783031210037
- Erscheinungsdatum: 20.02.2023
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 2.27 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
Kommentar zu "Toward Robots That Reason: Logic, Probability & Causal Laws / Synthesis Lectures on Artificial Intelligence and Machine Learning"
Schreiben Sie einen Kommentar zu "Toward Robots That Reason: Logic, Probability & Causal Laws / Synthesis Lectures on Artificial Intelligence and Machine Learning".
Kommentar verfassen