26 research outputs found

    Une approche pour supporter l'analyse qualitative des suites d'actions dans un environnement géographique virtuel et dynamique : l'analyse " What-if " comme exemple

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    Nous proposons une approche basĂ©e sur la gĂ©osimulation multi-agent et un outil d’aide Ă  la dĂ©cision pour supporter l’analyse « What-if » durant la planification des suites d’actions (plans) dans un environnement gĂ©ographique dynamique. Nous prĂ©sentons les caractĂ©ristiques du raisonnement « What-if » en tant 1) que simulation mentale 2) suivant un processus en trois Ă©tapes et 3) basĂ© sur du raisonnement causal qualitatif. Nous soulignons les limites de la cognition humaine pour appliquer ce raisonnement dans le cadre de la planification des suites d’actions dans un environnement gĂ©ographique dynamique et nous identifions les motivations de notre recherche. Ensuite, nous prĂ©sentons notre approche basĂ©e sur la gĂ©osimulation multi-agent et nous identifions ses caractĂ©ristiques. Nous traitons en particulier trois problĂ©matiques majeures. La premiĂšre problĂ©matique concerne la modĂ©lisation des phĂ©nomĂšnes gĂ©ographiques dynamiques. Nous soulignons les limites des approches existantes et nous prĂ©sentons notre modĂšle basĂ© sur le concept de situation spatio-temporelle que nous reprĂ©sentons en utilisant le formalisme de graphes conceptuels. En particulier, nous prĂ©sentons comment nous avons dĂ©fini ce concept en nous basant sur les archĂ©types cognitifs du linguiste J-P. DesclĂ©s. La deuxiĂšme problĂ©matique concerne la transformation des rĂ©sultats d’une gĂ©osimulation multi-agent en une reprĂ©sentation qualitative exprimĂ©e en termes de situations spatio-temporelles. Nous prĂ©sentons les Ă©tapes de traitement de donnĂ©es nĂ©cessaires pour effectuer cette transformation. La troisiĂšme problĂ©matique concerne l’infĂ©rence des relations causales entre des situations spatio-temporelles. En nous basant sur divers travaux traitant du raisonnement causal et de ses caractĂ©ristiques, nous proposons une solution basĂ©e sur des contraintes causales spatio-temporelles et de causalitĂ© pour Ă©tablir des relations de causation entre des situations spatio-temporelles. Finalement, nous prĂ©sentons MAGS-COA, une preuve de concept que nous avons implĂ©mentĂ©e pour Ă©valuer l’adĂ©quation de notre approche comme support Ă  la rĂ©solution de problĂšmes rĂ©els. Ainsi, les principales contributions de notre travail sont: 1- Une approche basĂ©e sur la gĂ©osimulation multi-agent pour supporter l’analyse « What-if » des suites d’actions dans des environnements gĂ©ographiques virtuels. 2- L’application d’un modĂšle issu de recherches en linguistique Ă  un problĂšme d’intĂ©rĂȘt pour la recherche en raisonnement spatial. 3- Un modĂšle qualitatif basĂ© sur les archĂ©types cognitifs pour modĂ©liser des situations dynamiques dans un environnement gĂ©ographique virtuel. 4- MAGS-COA, une plateforme de simulation et d’analyse qualitative des situations spatio-temporelles. 5- Un algorithme pour l’identification des relations causales entre des situations spatio-temporelles.We propose an approach and a tool based on multi-agent geosimulation techniques in order to support courses of action’s (COAs) “What if” analysis in the context of dynamic geographical environments. We present the characteristics of “What if” thinking as a three-step mental simulation process based on qualitative causal reasoning. We stress humans’ cognition limits of such a process in dynamic geographical contexts and we introduce our research motivations. Then we present our multi-agent geosimulation-based approach and we identify its characteristics. We address next three main problems. The first problem concerns modeling of dynamic geographical phenomena. We stress the limits of existing models and we present our model which is based on the concept of spatio-temporal situations. Particularly, we explain how we define our spatio-temporal situations based on the concept of cognitive archetypes proposed by the linguist J-P. DesclĂ©s. The second problem consists in transforming the results of multi-agent geosimulations into a qualitative representation expressed in terms of spatio-temporal situations and represented using the conceptual graphs formalism. We present the different steps required for such a transformation. The third problem concerns causal reasoning about spatio-temporal situations. In order to address this problem, we were inspired by works of causal reasoning research community to identify the constraints that must hold to identify causal relationships between spatio-temporal situations. These constraints are 1) knowledge about causality, 2) temporal causal constraints and 3) spatial causal constraints. These constraints are used to infer causal relationships among the results of multi-agent geosimulations. Finally, we present MAGS-COA, a proof on concept that we implemented in order to evaluate the suitability of our approach as a support to real problem solving. The main contributions of this thesis are: 1- An approach based on multi-agent geosimulation to support COA’s “What if” analysis in the context of virtual geographic environments. 2- The application of a model proposed in the linguistic research community to a problem of interest to spatial reasoning research community. 3- A qualitative model based on cognitive archetypes to model spatio-temporal situations. 4- MAGS-COA, a platform of simulation and qualitative analysis of spatio-temporal situations. 5- An algorithm to identify causal relationships between spatio-temporal situations

    ICT enabled participatory urban planning and policy development: The UrbanAPI project

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    Purpose: The aim of this paper is to present the effectiveness of participatory information and communication technology (ICT) tools for urban planning, in particular, supporting bottom-up decision-making in urban management and governance. Design/methodology/approach: This work begins with a presentation on the state of the art literature on the existing participatory approaches and their contribution to urban planning and the policymaking process. Furthermore, a case study, namely, the UrbanAPI project, is selected to identify new visualisation and simulation tools applied at different urban scales. These tools are applied in four different European cities - Vienna, Bologna, Vitoria-Gasteiz and Ruse - with the objective to identify the data needs for application development, commonalities in requirements of such participatory tools and their expected impact in policy and decision-making processes. Findings: The case study presents three planning applications: three-dimensional Virtual Reality at neighbourhood scale, Public Motion Explorer at city-wide scale and Urban Growth Simulation at city-region scale. UrbanAPI applications indicate both active and passive participation secured by applying these tools at different urban scales and hence facilitate evidence-based urban planning decision-making. Structured engagement with the city administrations indicates commonalities in user needs and application requirements creating the potential for the development of generic features in these ICT tools which can be applied to many other cities throughout Europe. Originality/value: This paper presents new ICT-enabled participatory urban planning tools at different urban scales to support collaborative decision-making and urban policy development. Various technologies are used for the development of these IT tools and applied to the real environment of four European cities. © Emerald Group Publishing Limited

    Modelling and Simulation of Human-Environment Interactions

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    Computational models provide intelligent environmental decision support systems to understand how human decisions are shaped by, and contribute to changes in, the environment. These models provide essential tools to tackle the important issues raised by climate change, including migrations and conflicts due to resource scarcity (e.g., water resources), while accounting for the necessity of co-managing ecosystems across a population of stakeholders with diverse goals. Such socio-environmental systems are characterized by their complexity, which is reflected by an abundance of open questions. This book explores several of these open questions, based on the contributions from over 50 authors. While several books account for methodological developments in modeling socio-environmental systems, our book is unique in combining case studies, methodological innovations, and a holistic approach to training the next generation of modelers. One chapter covers the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation. In another chapter, we show that the benefits of simulations are not limited to managing complex eco-systems, as they can also serve an educational mission in teaching essential rules and thus improve systems thinking competencies in the broader population

    Regional change in the Algarve: A Geographic Information System approach

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    Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information SystemsThe debate on sustainable development has led to an increasing interest covering the effects of the human beings on the natural environment. The development of information and communication technologies (ICT) allowed a better analysis of the drivers of environmental change. With the increase of ICT, especially related to monitoring of sustainable choices, methodologies for analysis of regional and local impact have made a significant contribution to the development of regional strategies at a policy level, but also contributed to the development of regional sciences. One of the main issues has been addressed by the analysis of carrying capacity and availability of scarce resources, resulting from a growing demand, leading to loss of vulnerable natural and historical areas. Much of the work of regional sciences has had a direct relation to space, due to the nature of socio-economic data. This thesis offers an integrated spatial assessment of the results of regional change brought by socio-economic growth. The Algarve region in Portugal is used as a laboratory to understand the current pressures and attempts to provide a framework for the future of socio-economic growth in the region and a systematic analysis of current pressures. While urban sprawl due to increasing tourist activity is an increasing concern, spatial analysis is used as an insightful tool for foresight of future change. Having considered that urban growth is a direct consequence of economic growth our research addresses the consequences of urban sprawl in the coastal region of the Algarve. By building up predictive tools for complex spatial system analysis, cellular automata are used to forecast future urban expansion in the region. The relationship of tourism to urban change is measured to assess what are true costs of tourism for the region. Tourism is then analysed within the duality of socio-economic pressures defining weak and strong sustainability. An integrated strategy considering the historical heritage of the Algarve is offered as a more interesting alternative to the current exploration of the marine environment. Thus, the dissertation expands on the usage of spatial analysis as tools to emphasize the importance of monitoring regional change in coastal environments from a socio-economic perspective. Geographic Information Systems are expressed as ubiquitous systems with unique properties to measure change and to offer relevant solutions for better decision making at local and regional level. An important asset of those tools in the context of information management is further explored in the capabilities of comparing results through spatial data manipulation and visualization of alternative futures for regional development

    Combining evolutionary algorithms and agent-based simulation for the development of urbanisation policies

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    Urban-planning authorities continually face the problem of optimising the allocation of green space over time in developing urban environments. To help in these decision-making processes, this thesis provides an empirical study of using evolutionary approaches to solve sequential decision making problems under uncertainty in stochastic environments. To achieve this goal, this work is underpinned by developing a theoretical framework based on the economic model of Alonso and the associated methodology for modelling spatial and temporal urban growth, in order to better understand the complexity inherent in this kind of system and to generate and improve relevant knowledge for the urban planning community. The model was hybridised with cellular automata and agent-based model and extended to encompass green space planning based on urban cost and satisfaction. Monte Carlo sampling techniques and the use of the urban model as a surrogate tool were the two main elements investigated and applied to overcome the noise and uncertainty derived from dealing with future trends and expectations. Once the evolutionary algorithms were equipped with these mechanisms, the problem under consideration was deïŹned and characterised as a type of adaptive submodular. Afterwards, the performance of a non-adaptive evolutionary approach with a random search and a very smart greedy algorithm was compared and in which way the complexity that is linked with the conïŹguration of the problem modiïŹes the performance of both algorithms was analysed. Later on, the application of very distinct frameworks incorporating evolutionary algorithm approaches for this problem was explored: (i) an ‘oïŹ„ine’ approach, in which a candidate solution encodes a complete set of decisions, which is then evaluated by full simulation, and (ii) an ‘online’ approach which involves a sequential series of optimizations, each making only a single decision, and starting its simulations from the endpoint of the previous run

    Assessing vulnerability and modelling assistance: using demographic indicators of vulnerability and agent-based modelling to explore emergency flooding relief response

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    Flooding is a significant concern for much of the UK and is recognised as a primary threat by most local councils. Those in society most often deemed vulnerable: the elderly, poor or sick, for example, often see their level of vulnerability increase during hazard events. A greater knowledge of the spatial distribution of vulnerability within communities is key to understanding how a population may be impacted by a hazard event. Vulnerability indices are regularly used – in conjunction with needs assessments and on-the-ground research – to target service provision and justify resource allocation. Past work on measuring and mapping vulnerability has been limited by a focus on income-related indicators, a lack of consideration of accessibility, and the reliance on proprietary data. The Open Source Vulnerability Index (OSVI) encompasses an extensive range of vulnerability indicators supported by the wider literature and expert validation and provides data at a sufficiently fine resolution that can identify vulnerable populations. Findings of the OSVI demonstrate the potential cascading impact of a flood hazard as it impacts an already vulnerable population: exacerbating pre-existing vulnerabilities, limiting capabilities and restricting accessibility and access to key services. The OSVI feeds into an agent-based model (ABM) that explores the capacity of the British Red Cross (BRC) to distribute relief during flood emergencies using strategies based upon the OSVI. A participatory modelling approach was utilised whereby the BRC were included in all aspects of the model development. The major contribution of this work is the novel synthesis of demographics analysis, vulnerability mapping and geospatial simulation. The project contributes to the growing understanding of vulnerability and response management within the NGO sector. It is hoped that the index and model produced will allow responder organisations to run simulations of similar emergency events and adjust strategic response plans accordingly

    Non-determinism in the narrative structure of video games

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    PhD ThesisAt the present time, computer games represent a finite interactive system. Even in their more experimental forms, the number of possible interactions between player and NPCs (non-player characters) and among NPCs and the game world has a finite number and is led by a deterministic system in which events can therefore be predicted. This implies that the story itself, seen as the series of events that will unfold during gameplay, is a closed system that can be predicted a priori. This study looks beyond this limitation, and identifies the elements needed for the emergence of a non-finite, emergent narrative structure. Two major contributions are offered through this research. The first contribution comes in the form of a clear categorization of the narrative structures embracing all video game production since the inception of the medium. In order to look for ways to generate a non-deterministic narrative in games, it is necessary to first gain a clear understanding of the current narrative structures implemented and how their impact on users’ experiencing of the story. While many studies have observed the storytelling aspect, no attempt has been made to systematically distinguish among the different ways designers decide how stories are told in games. The second contribution is guided by the following research question: Is it possible to incorporate non-determinism into the narrative structure of computer games? The hypothesis offered is that non-determinism can be incorporated by means of nonlinear dynamical systems in general and Cellular Automata in particular

    Sustainable Development

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    The technological advancement of our civilization has created a consumer society expanding faster than the planet's resources allow, with our resource and energy needs rising exponentially in the past century. Securing the future of the human race will require an improved understanding of the environment as well as of technological solutions, mindsets and behaviors in line with modes of development that the ecosphere of our planet can support. Sustainable development offers an approach that would be practical to fuse with the managerial strategies and assessment tools for policy and decision makers at the regional planning level
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