Machine Learning of Robot Assembly Plans

724,00 RON
+ 27,99 RON Livrare

Machine Learning of Robot Assembly Plans

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Machine Learning of Robot Assembly Plans

  • Marcă: Unbranded

724,00 RON

În stoc
+ 27,99 RON Livrare

Politica de retur pe 14 zile

Vândut de:

724,00 RON

În stoc
+ 27,99 RON Livrare

Politica de retur pe 14 zile

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Descriere

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. Language: English
  • Marcă: Unbranded
  • Categorie: Calcul și internet
  • Artist: Alberto Maria Segre
  • Limbă: English
  • Număr de pagini: 234
  • Format: Paperback
  • Data publicării: 2011/10/05
  • Editor / Etichetă: Springer
  • ID Fruugo: 337913974-741573425
  • ISBN: 9781461289548

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