Every year, the number of urban residents is growing. Diverse questions related to sustainability are rise from this growth. For example, for large and attractive territories, which urban planning policies to implement? How to manage and prevent technological or environmental hazards? Decision makers have to take all of these issues into account when defining their urban planning policies. Unfortunately, the assessment of the impacts of possible policies is difficult due to the complex and stochastic interplay between society and infrastructure. One of the most promising approaches to face this difficulty is agent-based modeling. This approach consists in modeling the studied system as a collection of interacting decision-making entities called agents. An agent-based model can provide relevant information about the dynamics of the real-world urban system it represents. Moreover, it can allow to be used as a virtual laboratory to test new urban planning policies. The use of agent-based models to study urban systems is booming for the last ten years. Another tendency is the development of more and more realist models. However, if models have make a lot of progresses concerning the integration of geographical and statistical data, the agents used to represent the different actors influencing the dynamic of the system (inhabitants, decision makers...) are often simplistic (reactive agents). Yet, for some urban models, being able to integrate this cognitive agents, i.e. agents able to make complex reasoning such as planning to achieve their goals, is mandatory to improve the realism of models and test new scenarios. Unfortunately, developing large-scale models that integrates cognitive agents requires high-level programming skills. Indeed, if there are nowadays several software platforms that propose to help modelers to define their agent-based models through a dedicated modeling language (Netlogo, GAMA…) or through a graphical interface (Starlogo TNG, Modelling4All, Repast Symphony, MAGéo...), none of them are adapted to the development of such models by modelers with low level programming skills: either they are too complex to use (Repast, GAMA) or too limited (Netlogo, Starlogo TNG, Modelling4All, Repast Symphony, MAGéo). As a result, geographers and urban planners that have no programming skills have to rely on computer scientists to develop models, what slows the development and the use of complex and realist spatial agent-based models. The objective of the ACTEUR project is to develop to help modelers, in particular geographers and urban planners, to design and calibrate through a graphical language cognitive agents able to act in a complex spatial environment. The platform has also for ambition to be used as a support of model discussion -participatory modeling- between the different actors concerned by a model (geographers, sociologists, urban planners, decision makers, representatives…). These tools will be integrated in the GAMA platform that enables to build large-scale models with thousands of hundreds of agents and that was already used to develop models with cognitive agents. In order to illustrate the utility and the importance of the developed tools, we will use them on two case studies. The first concerns the urban evolution of La Réunion island. The second case study will focus on the adaption to industrial hazards in Rouen. These two case studies are part of funded projects carried out by partners of the ACTEUR project.

Understanding how past societies responded to extreme climatic changes is crucial for gaining insight into current and future environmental challenges, especially environmental stress and sanitary conditions in the context of the present climate change impacting the Near-East. Evidence from paleoclimate data clearly indicates that climatic fluctuations in this area over the past millennium have not been homogeneous. Instead, a high degree of variability over time and across space is pointed out by hydrological changes in particular steep topography environments. These fluctuations were challenging for societies since precipitation variability can impact agriculture, food production but also sanitary conditions and the spread of disease. This project investigates the interaction between climate change and social responses since the medieval period in the poorly studied Near-East region, specifically on the island of Cyprus, and uses novel indicators for both climate and social vulnerability. On one hand, natural archives such as speleothems provide high-resolution and quantitative hydrological and temperature data to complement existing dendrochronology data as well as compiled weather data for the last century. Compilation of paleoclimate data will be transformed into climate maps of the island. On the other hand, the compiled public health archives of mortality and diseases together with past landscape maps offer new indicators to analyze social responses.

Vector-borne diseases (dengue, Zika, chikungunya) are an important public health issue. Understanding their transmission dynamics remains a major challenge at the sub-urban level. Indeed, environmental heterogeneities, variations in vector densities and daily mobility constitute a lock on the definition of epidemic risk indicators at this scale. MO3 therefore aims to (i) develop a simulation model to study the sensitivity of epidemic dynamics to targeted scenarios of anti-vector fights and (ii) evaluate in a large metropolis where dengue is endemic, Bangkok (Thailand), the effectiveness of these strategies. In cities where these diseases are endemic, our first hypothesis is that the urban territory has a limited number of places favorable to the maintenance of mosquito population during the inter-epidemic season, sufficient to ensure local, continuous and low-noise circulation of viruses. With seasonal changes (rising temperatures, monsoon rains), vector populations are exploding, increasing the risk of spreading viruses from these areas. Our second hypothesis is that the structuring of urban space (residence, economic and commercial activities, vegetated spaces) and the resulting discontinuities structure the daily mobilities of populations, and potentially the spread of pathogens in epidemic proportions. It is therefore essential to identify these potential reservoirs of pathogen diffusion early. Moreover, in cities where these diseases are not endemic, or not yet present, the dynamic mapping of the environmental risk based on the ecology of the mosquito must make it possible to identify and monitor the places and the periods favorable to the implantation and the proliferation of mosquito vectors. To achieve these objectives, the MO3 project will rely on differential equations and agent-based model, with high spatial and temporal resolution, to describe finely the urbanized space and the variety of dynamics that unfold there, those of vectors and human populations. Vector dynamics will be influenced by the spatial and temporal heterogeneity of their ecological niche, those of humans by their daily mobility, partly linked to their place of residence, their socio-economic profile and their age. The calibration of the model will be based on various data: satellite images, census, social networks, vector and epidemiological retrospective data. We also plan field surveys. Sites will be selected according to a value gradient of the ecological niche of the vector and a value gradient of centrality of the places. Weekly surveys over a 2-year period will be used to analyze the evolution of adult mosquito stocks with respect to these two indicators, and epidemiological surveys of at-risk populations will be used to assess exposure levels, according to these two indicators. All of this data will also be used to calibrate and validate the simulation model. Exploration methods based on evolutionary algorithms will be mobilized to evaluate, compare and hierarchize the mechanisms of the model with regard to simulated dynamics and observations that they can or must produce or reproduce. These methods will also evaluate and compare vector control strategies against the epidemiological dynamics simulated by the model, in search of the most effective strategy or strategies. MO3's ambition is therefore to develop a generic method that allows for vector-based struggles in priority areas, thus enabling local actors to optimally allocate their available but limited resources.

Populations are increasingly vulnerable to disastrous natural or technological events, as demographic and urban growth lead to greater exposures of goods and people. Large scale evacuation strategies are efficient tools for mitigating this vulnerability. Nonetheless, risks incurred during an important displacement through an altered environment are high: refusal to evacuate, crashes, direct exposure to the source hazard, riots, emergency services failures… In France a policy called Territoires à Risques importants d’Inondation (TRI) has emerged to deal with floods, in a first step to deal with the most frequent natural disaster in this country. Nevertheless, local governments and emergency managers lack prospective tools to assist their understanding and planning of large scale evacuations. ESCAPE aims at overcoming this major problem by the creation of an evacuation operational research system. The core of our project is the tight coupling between Geographical Information Systems, agent-based multiscale modelling and computer simulation exploring tools. It will be deployed and validated on real case studies, so as to generate simulations realistic enough to allow their use by emergency managers for experimenting evacuation strategies. By combining sources including territorial information (land occupation, transport networks, hazards expansion and intensity), demographic data (residential and transitional population numbers, age pyramid), a mobilityand traffic management simulator (cars, bikes, pedestrians, public transport), and by providing different evacuation strategies (partial or complete, by waves or synchronous), we will provide measures on evacuation time of various crisis zones, and will make explicit local and global constraints on these times. For that, we need to explore at multiple space and time scales the emergence of collective behaviours that would detract from planned strategies, and to devise solutions to dampen the consequences of these behaviours on the evacuation times. The ESCAPE team will build demonstrators to allow productive interactions with emergency services and remain reality-grounded for the whole duration of the project. These prototypes will allow us to precisely identify the stakes at play in each case study and the needs of the various managers.

Sociological and economic research and political debates in India continue to focus on the role of social groups in shaping disparities across the country. However, existing research often fails to capture the true complexity of India's social structure, which includes hundreds of distinct communities. Communities and Territories in India is a big-data, multidisciplinary project to revisit India's social disparity debate with new disaggregated data that include self-declared community membership. We will construct a unique individual and community dataset linked to a wealth of social, demographic, and economic indicators. The project is complemented by field-based research on contextual knowledge production to understand the mechanisms of social identity designation. This new dataset on community identity should constitute a turning point for studying India's social fabric as it provides disaggregated data on social groups across India. Our research will first project a unique disaggregated picture of India's social structure. The project will also reassess the crucial role of community affiliation in determining current socioeconomic, gender, demographic, and health disparities. Finally, web-based tools, a final conference, and scientific production will widely disseminate data and research outputs. The work program rests on successive phases of data acquisition, field surveys, spatial and socioeconomic analysis, and data sharing, following the project's core objectives: Objective 1: to produce a detailed database of social groups using mixed methods and participative research. Objective 2: to understand the process of social identity formation Objective 3: to map disaggregated social groups that are the cornerstone of India's social fabric. Objective 4: to reassess the contribution of social groups to sociodemographic and economic disparities beyond the usual official categories. Objective 5: to engage academic and civil society stakeholders and disseminate results.