1 Introduction. - 1. 1 Background. - 1. 2 NGE and other exemplar-based theories. - 1. 3 Previous models. - 1. 4 Comparisons of NGE and other models. - 1. 5 Types of generalization. - 2 The NGE learning algorithm. - 2. 1 Initialization. - 2. 2 Get the next example. - 2. 3 Make a prediction. - 2. 4 Feedback. - 2. 5 Summary of algorithm. - 2. 6 Partitioning feature space. - 2. 7 Assumptions. - 2. 8 Greedy variant of the algorithm. - 3 Review. - 3. 1 Concept learning in psychology. - 3. 2 Prototype theory and exemplar theory. - 3. 3 Each as a multiple prototype model. - 3. 4 Machine learning in AI. - 3. 5 Connectionism. - 3. 6 Cluster analysis. - 3. 7 Conclusion. - 4 Experimental results with NGE. - 4. 1 Breast cancer data. - 4. 2 Iris classification. - 4. 3 Echocardiogram tests. - 4. 4 Discrete event simulation. - 5 Conclusion. - 5. 1 Weight factors. - 5. 2 Synthesis with explanation-based learning. - 5. 3 Psychological plausibility. - 5. 4 Complexity results. - 5. 5 Future experimental work. - A Data sets. - A. 1 Breast cancer data. - A. 2 Iris data. - A. 3 Echocardiogram data. Language: English