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Weitnauer, Erik: Interactions between perception and rule-construction in human and machine concept learning. 2016
Inhalt
Abstract
Publications
Acknowledgments
Contents
1 Introduction
1.1 Motivation
1.2 Physical Bongard Problems (PBPs)
PBPs for Cognitive Research
1.3 How Concepts Are Learned
Machine Learners
Human Learners and Cognitive Models
Summary
2 Perceiving Physical Scenes
2.1 Feature Space
2.2 Physical Features
Stability
Support
Movability
2.3 Spatial Relations
Related Work
Fuzzy Spatial Relations
Fuzzy Landscape Algorithm
Bipolar Fuzzy Landscapes
Combining Spatial Concepts
2.4 Group Attributes
2.5 Conclusion
3 Learning Physical Concepts
3.1 Guiding Principles of Model Design
3.2 Implementation
Scenes
Switching Between Active Scenes
Objects and Groups
Features and Percepts
Selectors
Hypotheses
Attention Mechanisms
Actions
3.3 Utility Estimation
Hypotheses
Objects and Groups
Features
3.4 A Problem Solution Walkthrough
3.5 Conclusion
4 Human Performance on PBPs
4.1 The Role of Similarity in Concept Learning
4.2 Eye Tracking Study
4.3 Scene Ordering Experiments
Amazon Mechanical Turk as Research Platform
1st Experiment
2nd Experiment
3rd Experiment
4th Experiment
4.4 General Discussion
5 Model Performance on PBPs
5.1 Experimental Setup
5.2 Results
Reaction Time Distribution
Performance Correlation per Problem
Influence of Presentation Condition
Efficiency
5.3 Discussion
Agreements with Human Results
Disagreements with Human Results
6 Conclusion
A List of Physical Bongard Problems
Bibliography