Vor Ort
Merkzettel Warenkorb
Produktbild: Machine Learning of Robot Assembly Plans
Band 51

Machine Learning of Robot Assembly Plans

Aus der Reihe Springer International Series in Engineering and Computer

97,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.10.2011

Abbildungen

XVIII, 234 p.

Verlag

Springer Us

Seitenzahl

234

Maße (L/B/H)

23,5/15,5/1,5 cm

Gewicht

394 g

Auflage

Softcover reprint of the original 1st ed. 1988

Sprache

Englisch

ISBN

978-1-4612-8954-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

05.10.2011

Abbildungen

XVIII, 234 p.

Verlag

Springer Us

Seitenzahl

234

Maße (L/B/H)

23,5/15,5/1,5 cm

Gewicht

394 g

Auflage

Softcover reprint of the original 1st ed. 1988

Sprache

Englisch

ISBN

978-1-4612-8954-8

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Machine Learning of Robot Assembly Plans
  • 1 Introduction.- 1.1. Machine Learning.- 1.2. Robotics.- 1.3. About the Book.- 2 Scenario.- 2.1. Preliminaries.- 2.2. Specifying the Problem.- 2.3. Attempting to Solve the Problem.- 2.4. Observing the Expert’s Plan.- 2.5. Generalizing the Solution.- 2.6. Solving the Same Problem After Learning.- 2.7. Solving Similar Problems After Learning.- 3 Explanation-Based Learning.- 3.1. Similarity-Based Learning.- 3.2. Learning-Apprentice Systems.- 3.3. Explanation-Based Learning.- 3.4. A Prototypical EBL System.- 3.5. Issues for EBL Systems.- 4 The Arms World.- 4.1. Characterizing the Robot World.- 4.2. Simulating the Robot World.- 5 Learning And Problem Solving.- 5.1. Knowledge Representation.- 5.2. The Performance Element.- 5.3. The Learning Element.- 6 The Arms Implementation.- 6.1. A Note About the Implementation Language.- 6.2. Optimization Tools.- 6.3. Implementing the Solid Modeler.- 6.4. Implementing the Graphics Subsystem.- 6.5. Implementing the Schema System.- 6.6. Implementing the Top Level.- 7 Scenario Revisited.- 7.1. Attempting to Solve the Problem.- 7.2. Observing the Expert’s Plan.- 7.3. Verifying the Solution.- 7.4. Generalizing the Solution.- 7.5. Solving the Same Problem After Learning.- 7.6. Solving Similar Problems After Learning.- 7.7. Observing Similar Problems After Learning.- 8 Summary And Future Work.- 8.1. Relation to Other Work.- 8.2. Extensibility of ARMS.- 8.3. Future Research Directions.- 8.4. Conclusions.- Appendix A Solid Modeling Systems.- Appendix B Schema Semantics.- Appendix C A Simpler Example.- C.1. Describing the Initial State.- C.2. Attempting to Solve the Problem.- C.3. Observing the Expert’s Plan.- C.4. Verifying the Solution.- C.5. Generalizing the Solution.- C.6. Solving the Same Problem After Learning.- C.7. Solving SimilarProblems After Learning.- C.8. Observing Similar Problems After Learning.- Appendix D A More Complex Example.- D.1. Describing the Initial State.- D.2. Attempting to Solve the Problem.- D.3. Observing the Expert’s Plan.- D.4. Verifying the Solution.- D.5. Generalizing the Solution.- D.5.1. A More General New Schema.- D.5.2. A More Operational New Schema.- D.6. Solving the Same Problem After Learning.- D.7. Solving Similar Problems After Learning.- Appendix E Performance Considerations.- E.1. Learning Episode 1.- E.2. Problem-Solving Episode 1.- E.3. Problem-Solving Episode 2.- E.4. Problem-Solving Episode 3.- E.5. Problem-Solving Episode 4.- E.6. Learning Episode 2.- E.7. Learning Episode 3.- E.8. Problem-Solving Episode 5.- E.9. Problem-Solving Episode 6.- Appendix F Built-in Schemata.- F.1. State Schemata.- F.1.1. Joint Schemata.- F.1.2. Degree of Freedom Schemata.- F.1.3. Constraint Schemata.- F.2. Operator Schemata.- F.2.1. Primitive Operator Schemata.- References.