Machine Learning Methods for Planning (PDF)
(Sprache: Englisch)
Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree,...
sofort als Download lieferbar
eBook (pdf)
Fr. 106.90
inkl. MwSt.
- Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Machine Learning Methods for Planning (PDF)“
Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.
Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search.
This book is a valuable resource for production managers, planners, scientists, and research workers.
Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credit assignment and describe tractable classes of problems for which optimal plans can be derived. This book discusses as well how reactive, integrated systems give rise to new requirements and opportunities for machine learning. The final chapter deals with a method for learning problem decompositions, which is based on an idealized model of efficiency for problem-reduction search.
This book is a valuable resource for production managers, planners, scientists, and research workers.
Bibliographische Angaben
- 2014, 554 Seiten, Englisch
- Herausgegeben: Steven Minton
- Verlag: Elsevier Science & Techn.
- ISBN-10: 1483221172
- ISBN-13: 9781483221175
- Erscheinungsdatum: 12.05.2014
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Grösse: 36 MB
- Mit Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
Kopierschutz
Dieses eBook können Sie uneingeschränkt auf allen Geräten der tolino Familie lesen. Zum Lesen auf sonstigen eReadern und am PC benötigen Sie eine Adobe ID.
Kommentar zu "Machine Learning Methods for Planning"
0 Gebrauchte Artikel zu „Machine Learning Methods for Planning“
| Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
|---|
Schreiben Sie einen Kommentar zu "Machine Learning Methods for Planning".
Kommentar verfassen