Beschreibung
10.2 Summary of Ideas. 256 10.2.1 Spatial Behavior As Rules For Decision Making. 258 10.2.2. Cognitive Mapping. 258 10.2.3. Storing Information. ". 260 10.2.4. Searching. 260 10.2.5. Learning. 261 10.2.6. Judging Similarity. 261 10.2.7 Neural Geographic Information Science (NGIS). 262 REFERENCES. 265 INDEX. 279 ACKNOWLEDGEMENTS. 287 x LIST OF TABLES Table 8.1: The types of similarity comparisons created for the experiment to determine the effect ofx as a first or second common or distinctive feature (Lloyd, Rostkowska-Covington, and Steinke 1996). Table 9.1: Data used to compute the gravity model using regression and a neural network. Data for all variables are scaled so that the highest value equals 0.9 and the lowest value equals 0.1. Table 9.2: Class means for 11 socio-economic and life-cycle variables for the Black, Integrated, and White classes. Table 9.3: Weights for neuron at row 5 and column 1 that learned the blue horizontal rectangle map symbol. LIST OF FIGURES Figure 1.1: Spatial cognition is a research area of interest for both geography and psychology. Both disciplines are interested in fundamental ideas related to encoding processes, internal representations, and decoding processes. Figure 1.2: The place names on this map of New Orleans depict the propositions used for navigation by local residents. A similar map appeared in the June 30, 1991, edition of The Times-Picayune.
Inhalt
1: Geography and Cognitive Science. 1.1. Introduction. 1.2. Cognitive Processing. 1.3. Conclusions. 2: A Connectionist Approach to Spatial Cognition. 2.1. Introduction. 2.2. Memory Hardware. 2.3. Map Reading. 2.4. Analyzers. 2.5. Types of Memory. 2.6. Episodic Analyzer. 2.7. Action System. 2.8. Interacting Systems. 2.9. Fuzzy Cognitive Maps. 2.10. Interactive Activation Competition Models. 2.11. Interaction Activation Competition Model as Cognitive Map. 2.12. Conclusions. 3: Cognitive Maps. 3.1. Introduction. 3.2. Encoding Processes. 3.3. Conclusions. 4: Storing Spatial Information in Memory. 4.1. Introduction. 4.2. Object Files. 4.3. Mental Models. 4.4. Conclusions. 5: Spatial Search Processes. 5.1. Introduction. 5.2. Cognitive Theories of Search. 5.3. Geographic Applications. 5.4. Conclusions. 6: Learning Geographic Information. 6.1. Introduction. 6.2. Learning Categories. 6.3. Climate Categories. 6.4. Learning Higher-Order Categories. 6.5. The Organization of Geographic Information. 6.6. Conclusions. 7: Spatial Prototypes. 7.1. Introduction. 7.2. Category Prototypes. 7.3. Using Prototypes. 7.4. When is What Where? 7.5. Conclusions. 8: Similarity. 8.1. Introduction. 8.2. Comparing Maps. 8.3. Theoretical Similarity of Maps. 8.4. Conclusions. 9: Neural Network Applications. 9.1. Introduction. 9.2. Types of Problems. 9.3. The Gravity Model. 9.4. Residential Integration. 9.5. Acquiring Spatial Information. 9.6. Pattern Recognition. 9.7. Conclusions. 10: Conclusions. 10.1. Introduction. 10.2. Summary of Ideas. References. Index.
