A Conceptual Model of Exploration Wayfinding: An Integrated Theoretical Framework and Computational Methodology

This thesis is an attempt to integrate contending cognitive approaches to modeling wayfinding behavior. The primary goal is to create a plausible model for exploration tasks within indoor environments. This conceptual model can be extended for practical applications in the design, planning, and Social sciences. Using empirical evidence a cognitive schema is designed that accounts for perceptual and behavioral preferences in pedestrian navigation. Using this created schema, as a guiding framework, the use of network analysis and space syntax act as a computational methods to simulate human exploration wayfinding in unfamiliar indoor environments. The conceptual model provided is then implemented in two ways. First of which is by updating an existing agent-based modeling software directly. The second means of deploying the model is using a spatial interaction model that distributed visual attraction and movement permeability across a graph-representation of building floor plans

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

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Prepared for Annual Reviews of Economics.

Inductive Pattern Formation

With the extended computational limits of algorithmic recursion, scientific investigation is transitioning away from computationally decidable problems and beginning to address computationally undecidable complexity. The analysis of deductive inference in structure-property models are yielding to the synthesis of inductive inference in process-structure simulations. Process-structure modeling has examined external order parameters of inductive pattern formation, but investigation of the internal order parameters of self-organization have been hampered by the lack of a mathematical formalism with the ability to quantitatively define a specific configuration of points. This investigation addressed this issue of quantitative synthesis. Local space was developed by the Poincare inflation of a set of points to construct neighborhood intersections, defining topological distance and introducing situated Boolean topology as a local replacement for point-set topology. Parallel development of the local semi-metric topological space, the local semi-metric probability space, and the local metric space of a set of points provides a triangulation of connectivity measures to define the quantitative architectural identity of a configuration and structure independent axes of a structural configuration space. The recursive sequence of intersections constructs a probabilistic discrete spacetime model of interacting fields to define the internal order parameters of self-organization, with order parameters external to the configuration modeled by adjusting the morphological parameters of individual neighborhoods and the interplay of excitatory and inhibitory point sets. The evolutionary trajectory of a configuration maps the development of specific hierarchical structure that is emergent from a specific set of initial conditions, with nested boundaries signaling the nonlinear properties of local causative configurations. This exploration of architectural configuration space concluded with initial process-structure-property models of deductive and inductive inference spaces. In the computationally undecidable problem of human niche construction, an adaptive-inductive pattern formation model with predictive control organized the bipartite recursion between an information structure and its physical expression as hierarchical ensembles of artificial neural network-like structures. The union of architectural identity and bipartite recursion generates a predictive structural model of an evolutionary design process, offering an alternative to the limitations of cognitive descriptive modeling. The low computational complexity of these models enable them to be embedded in physical constructions to create the artificial life forms of a real-time autonomously adaptive human habitat

Tractable Fragments of Temporal Sequences of Topological Information

In this paper, we focus on qualitative temporal sequences of topological information. We firstly consider the context of topological temporal sequences of length greater than 3 describing the evolution of regions at consecutive time points. We show that there is no Cartesian subclass containing all the basic relations and the universal relation for which the algebraic closure decides satisfiability. However, we identify some tractable subclasses, by giving up the relations containing the non-tangential proper part relation and not containing the tangential proper part relation. We then formalize an alternative semantics for temporal sequences. We place ourselves in the context of the topological temporal sequences describing the evolution of regions on a partition of time (i.e. an alternation of instants and intervals). In this context, we identify large tractable fragments

Fuzzy cognitive mapping to support multi-agent decisions in development of urban policymaking

The awareness about environmental complexity involves real-time knowledge and demands urban planning initiatives. Knowledge is multiform, multi-agent and mirrors environmental complexity. Problems characterizing urban sustainability particularly claim non-expert knowledge, being informal, puzzling, uncertain, incomplete, hard to be handled, formalized, modelled. This study utilizes Fuzzy cognitive maps to explore such complexity and support multiagent decisions. It concerns the scenario-building process of the new plan of Taranto (Italy), a paradigmatic example of decaying industrial area, heavily characterized by social fragmentation and environment degradation. This approach aims at structuring environmental problems, modelling future strategies and contributing to build a multi-agent decision support system for complex urban planning contexts

Urban segregation as a complex system : an agent-based simulation approach

Urban segregation represents a significant barrier for achieving social inclusion in cities. To overcome this, it is necessary to implement policies founded upon a better understanding of segregation dynamics. However, a crucial challenge for achieving such understanding lies in the fact that segregation is a complex system. It emerges from local interactions able to produce unexpected and counterintuitive outcomes that cannot be defined a priori. This study adopts an agent-based simulation approach that addresses the complex nature of segregation. It proposes a model named MASUS, Multi-Agent Simulator for Urban Segregation, which provides a virtual laboratory for exploring theoretical issues and policy approaches concerning segregation. The MASUS model was first implemented for São José dos Campos, a medium-sized Brazilian city. Based on the data of this city, the model was parameterized and calibrated. The potential of MASUS is demonstrated through three different sets of simulation experiments. The first compares simulated data with real data, the second tests theories about segregation, and the third explores the impact of anti-segregation policies. The first set of experiments provides a retrospective validation of the model by simulating the segregation dynamics of São José dos Campos during the period 1991-2000. In general, simulated and real data reveal the same trends, a result that demonstrates that the model is able to accurately represent the segregation dynamics of the study area. The second set of experiments aims at demonstrating the potential of the model to explore and test theoretical issues about urban segregation. These experiments explore the impact of two mechanisms on segregation: income inequality and personal preferences. To test the impact of income inequality, scenarios considering different income distributions were simulated and compared. The results show how decreasing levels of income inequality promote the spatial integration of different social groups in the city. Additional tests were conducted to explore how the preferences of high-income families regarding the presence of other income groups could affect segregation patterns. The results reveal that the high levels of segregation were maintained even in a scenario where affluent households did not take into account the income composition of neighborhoods when selecting their residential location. Finally, the third set of experiments provides new insights about the impact of different urban policies on segregation. One experiment tests whether the regularization of clandestine settlements and equitable distribution of infrastructure would affect the segregation trends in the city. The simulated outputs indicate that they had no significant impact on the segregation patterns. Besides this test focusing on a general urban policy, two specific social-mix policy approaches were explored: poverty dispersion and wealth dispersion. The results suggest that policies based on poverty dispersion, which have been adopted in cities in Europe and the United States, are less effective in developing countries, where poor families represent a large share of the population. On the other hand, the policy based on wealth dispersion was able to produce substantial and long-term improvements in the segregation patterns of the city.Städtische Segregation als komplexes System : Ein agentenbasierter Simulationsansatz Die städtische Segregation stellt eine bedeutende Barriere für die Erreichung der sozialen Inclusion in den Städten dar. Um diese zu überwinden, ist es notwendig, eine Politik zu betreiben, die die Dynamiken der Segregation besser versteht und berücksichtigt. Eine besondere Herausforderung für ein besseres Verständnis dieser Dynamik ist die Tatsache, dass Segregation ein komplexes System ist. Dieses System entsteht aus lokalen Interaktionen, die zu unerwarteten und nicht eingängigen Ergebnissen führt, die nicht von vornherein bestimmt werden können. Diese Studie wendet einen multi-agenten Simulationsmodel an, das die komplexe Natur der Segregation berücksichtigt. Es schlägt ein Modell mit dem Namen MASUS (Multi-Agent Simulator for Urban Segregation) vor. Dieses bietet ein virtuelles Labor für die Untersuchung der theoretischen Aspekte und Politikansätze der Segregation. Das Modell wurde für São José dos Campos, eine mittelgroße brasilianische Stadt, eingesetzt. Das Modell wurde auf der Grundlage der Daten dieser Stadt parametisiert und kallibriert. Das Potenzial von MASUS wird durch drei verschiedene Arten von Simulationsexperimente dargestellt. Die erste vergleicht simulierte Daten mit realen Daten, die zweite prüft Segregationstheorien, und die dritte untersucht die Auswirkungen von Antisegregationspolitik. Die erste Gruppe von Experimenten liefert eine rückblickende Validierung des Modells durch die Simulation der Segregationsdynamiken von São José dos Campos im Zeitraum 1991-2000. Die simulierten und realen Daten zeigen im Allgemeinen die gleichen Trends. Dies zeigt, dass das Modell in der Lage ist, die Segregationsdynamik im Untersuchungsgebiet korrekt darzustellen. Die zweite Gruppe von Experimenten hat zum Ziel, das Potenzial des Modells hinsichtlich der Untersuchung und Prüfung der theoretischen Aspekte städtischer Segregation darzustellen. Diese Experimente untersuchen die Auswirkung von zwei Mechanismen auf Segregation: Einkommensungleichheit und persönliche Präferenzen. Um die Auswirkungen von Einkommensungleichheit zu prüfen, wurden Szenarien mit unterschiedlichen Einkommensverteilungen simuliert und verglichen. Die Ergebnisse zeigen wie abnehmende Einkommenshöhen die räumliche Integration von verschiedenen sozialen Gruppen in der Stadt fördern. Zusätzliche Tests wurden durchgeführt, um zu untersuchen wie die Präferenzen von Haushalten mit hohen Einkommen im Bezug auf das Vorhandensein anderer Einkommensgruppen die Segregationsmuster beeinflussen könnten. Die Ergebnisse zeigen, dass die Segregation auf hohem Niveau blieb sogar in einem Szenario wo wohlhabende Haushalte das Einkommensgefüge der Nachbarschaft bei der Wahl ihrer Wohngegend nicht berücksichtigten. Die dritte Gruppe von Experimenten führt zu neuen Einsichten über die Auswirkungen von verschiedenen städtischen politischen Maßnahmen auf die Segregation. Ein Experiment prüft ob die Regulierung von illegalen Siedlungen und die gleichmäßige Verteilung der Infrastruktur die Segregationstrends in der Stadt beeinflussen. Die Ergebnisse der Simulation zeigen, dass diese keine signifikante Auswirkung auf die Segregationsmuster haben. Neben diesem Test, der die allgemeine städtische Politik zum Inhalt hat, wurden zwei Ansätze der spezifischen Sozialen-Mix-Politik untersucht: Armutsverteilung und Wohlstandsverteilung. Die Ergebnisse deuten daraufhin, dass eine Politik der Armutsverteilung, die aus europäischen und nordamerikanischen Städten bekannt ist, weniger wirkungsvoll in Entwicklungsländern ist, wo arme Familien einen Großteil der Bevölkerung darstellen. Auf der anderen Seite führte eine Politik der Wohlstandsverteilung zu erheblichen und langfristigen Verbesserungen der Segregationsmuster der Stadt

Examining the Relationship Between Road Structure and Burglary Risk Via Quantitative Network Analysis

OBJECTIVES: To test the hypothesis that the spatial distribution of residential burglary is shaped by the configuration of the street network, as predicted by, for example, crime pattern theory. In particular, the study examines whether burglary risk is higher on street segments with higher usage potential. METHODS: Residential burglary data for Birmingham (UK) are examined at the street segment level using a hierarchical linear model. Estimates of the usage of street segments are derived from the graph theoretical metric of betweenness, which measures how frequently segments feature in the shortest paths (those most likely to be used) through the network. Several variants of betweenness are considered. The geometry of street segments is also incorporated—via a measure of their linearity—as are several socio-demographic factors. RESULTS: As anticipated by theory, the measure of betweenness was found to be a highly-significant predictor of the burglary victimization count at the street segment level for all but one of the variants considered. The non-significant result was found for the most localized measure of betweenness considered. More linear streets were generally found to be at lower risk of victimization. CONCLUSIONS: Betweenness offers a more granular and objective means of measuring the street network than categorical classifications previously used, and its meaning links more directly to theory. The results provide support for crime pattern theory, suggesting a higher risk of burglary for streets with more potential usage. The apparent negative effect of linearity suggests the need for further research into the visual component of target choice, and the role of guardianship