Simulation of Complex Systems in GIS

<p>General Introduction xi</p>
<p>PART 1. THE STRUCTURE OF THE GEOGRAPHIC SPACE 1</p>
<p>Part 1. Introduction 3</p>
<p>Chapter 1. Structure and System Concepts 5</p>
<p>1.1. The notion of structure 5</p>
<p>1.2. The systemic paradigm 10</p>
<p>1.3. The notion of organization 13</p>
<p>Chapter 2. Space and Geometry 29</p>
<p>2.1. Different theories of space 29</p>
<p>2.2. Geometry and its data structures 43</p>
<p>2.3. Neat geometry and fuzzy geometry 60</p>
<p>Chapter 3. Topological Structures: How Objects are Organized in Spatial Systems 67</p>
<p>3.1. Topology 67</p>
<p>3.2. Metrics and topologies 68</p>
<p>3.3. Calculated topology, structural topology 71</p>
<p>3.4. Hierarchization 78</p>
<p>Chapter 4. Matter and Geographical Objects 79</p>
<p>4.1. Geographic matter 79</p>
<p>4.2. The notion of observation 82</p>
<p>4.3. The geographic object: Definitions and principles 84</p>
<p>Chapter 5. Time and Dynamics 97</p>
<p>5.1. Time 97</p>
<p>5.2. Temporalities 100</p>
<p>5.3. Events, processes 105</p>
<p>5.4. Decomposition of a complex process 115</p>
<p>5.5. An epistemic choice: reciprocal dependency between the complexity levels of a phenomenon 117</p>
<p>Chapter 6. Spatial Interaction 121</p>
<p>6.1. Presentation of the concept 121</p>
<p>6.2. Definition of macroscopic interaction 125</p>
<p>6.3. The four elementary (inter)actions 127</p>
<p>6.4. Microscopic interaction like a multigraph 128</p>
<p>6.5. Composition of successive interactions 130</p>
<p>6.6. The configurations and the trajectories of a simulation are categories 131</p>
<p>6.7. Intermediary level matrix representation 133</p>
<p>6.8. Examples of interactions 134</p>
<p>6.9. First definition of the notion of spatial system 138</p>
<p>Part 1. Conclusion: Stages of the Ontogenesis 141</p>
<p>PART 2. MODELING THROUGH CELLULAR AUTOMATA 145</p>
<p>Chapter 7. Concept and Formalization of a CA 147</p>
<p>7.1. Cellular automata paradigm 148</p>
<p>7.2. Notion of finite–state automata 150</p>
<p>7.3. Mealy and Moore automata 151</p>
<p>7.4. A simple example of CA: the game of life 152</p>
<p>7.5. Different decompositions of the functions of a cell 153</p>
<p>7.6. Threshold automaton, window automaton 155</p>
<p>7.7. Micro level and Stochastic automaton 156</p>
<p>7.8. Macro level and deterministic automaton 156</p>
<p>7.9. General definition of a geographic cellular automaton 157</p>
<p>7.10. Different scheduling regimes of the internal tasks of the system 160</p>
<p>7.11. Ports, channels, encapsulation 162</p>
<p>7.12. Interaction 164</p>
<p>7.13. Space associated with a geographic cellular automaton 168</p>
<p>7.14. Topology and neighborhood operator of a GCA 168</p>
<p>7.15. The notion of cellular layer 168</p>
<p>7.16. Hierarchized GCA models 169</p>
<p>Chapter 8. Examples of Geographic Cellular Automaton Models 171</p>
<p>8.1. SpaCelle, multi–layer cellular automaton 172</p>
<p>8.2. Example: the evolution model of the Rouen agglomeration 181</p>
<p>8.3. RuiCells 189</p>
<p>8.4. GeoCells 207</p>
<p>Part 2. Conclusion 235</p>
<p>PART 3. A GENERAL MODEL OF GEOGRAPHIC AGENT SYSTEMS 237</p>
<p>Part 3. Introduction 239</p>
<p>Chapter 9. Theoretical Approach of an Integrated Simulation Platform 241</p>
<p>9.1. For an integrated platform of simulation 241</p>
<p>9.2. General specifications 242</p>
<p>Chapter 10. A Formal Ontology of Geographic Agent Systems 245</p>
<p>10.1. The conceptual framework 245</p>
<p>10.2. The notion of a geographic agent system 247</p>
<p>10.3. A generalization of the notion of process 249</p>
<p>10.4. The notion of a geographic agent 250</p>
<p>10.5. The formalization of the notion of organization 258</p>
<p>10.6. The formalization of behavior 268</p>
<p>10.7. Formalization of a general AOC model 279</p>
<p>10.8. The Schelling model example 280</p>
<p>Part 3. Conclusion 283</p>
<p>General Conclusion 285</p>
<p>Acronyms 291</p>
<p>Bibliography 293</p>
<p>Index 299</p>