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Academic literature on the topic 'Planification distribuée , Développement'
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Journal articles on the topic "Planification distribuée , Développement"
El Faiz, Abdelouahed, Hanane Dounas, Abdelilah Meddich, Mohamed Hafidi, and Ahmed Ouhammou. "Biodiversité des espaces verts publics de la commune urbaine de Marrakech (CUM) (Maroc). Biodiversity of the public green spaces in the Urban District of Marrakesh (UDM) (Morocco)." Acta Botanica Malacitana 41 (December 1, 2016): 83–100. http://dx.doi.org/10.24310/abm.v41i0.2455.
Full textEl Faiz, Abdelouahed, Hanane Dounas, Abdelilah Meddich, Mohamed Hafidi, and Ahmed Ouhammou. "Biodiversité des espaces verts publics de la commune urbaine de Marrakech (CUM) (Maroc). Biodiversity of the public green spaces in the Urban District of Marrakesh (UDM) (Morocco)." Acta Botanica Malacitana 41 (May 25, 2017): 83. http://dx.doi.org/10.24310/actabotanicaabm.v41i0.2455.
Full textDissertations / Theses on the topic "Planification distribuée , Développement"
Clerc, Xavier. "Planification dans un espace de buts par stratégie de type meilleur d'abord." Grenoble INPG, 2007. http://www.theses.fr/2007INPG0059.
Full textMost of distributed planning systems are based on models which were developped for centralized planning. These models have then been adapted to distribution and its specific contraints. Our goal is at the opposite to design a planning model that considers these constraints as premises. We have developped a planning model that uses a best-first search (as an adaptation of the proof-number search algorithm). We have applied this model to planning over task structures (from multiagent notations) as well as to HTN planning. Ln this latter case, we have shown how a best-first search allows the planner to rapidly gather constraints that can prune branches from the search space. We have also defined plan robustness in order to mitigate the consequences of an agent failure or a resource unavailability
Pluchinotta, Irene. "Multi-Agent Modelling for Distributed Intelligent Decision in Water Management." Thesis, Paris 9, 2015. http://www.theses.fr/2015PA090006.
Full textWater resource management can be a complex, uncertain and conflictual domain. It faces numerous problems in many regions of the world, such as the disparity of interests associated with the water resource, multiple decision makers, complex networks of administration, inoperative water distribution, various socio-political events and climate change. Consequently, environmental decision-making takes place in a highly interconnected system, in which neither the decisional ramifications nor the complexity of its impacts can be neglected. In the Apulia Region, water scarcity is the main rising problem and is affecting human and more-than-human communities.Water scarcity generates the need to enhance collaborative multi-agent decision-making processes. Researchers suggest that the “tragedy of commons” could be avoided when a shared resource is at stake, provided that communities interact and operate in a collective way and avoid, for example, the market rules constraints. This requires the development of dynamic decision-aiding tools. They should be capable to integrate the different problem frames held by the decision makers, to clarify the differences among those frames, to support the creation of a collaborative problem structuring process and to provide shared platforms and interaction spaces.In this regard, we built a dynamic interaction space (DIS), highlighting the operative criticalities and allowing the analysts to identify a shared problem definition. The emerging issues of gathering and exchanging knowledge and representing structured concepts can be solved through a combined approach. Multi-agent systems joined with system dynamics can provide unconventional alternatives that use physical and social components, with a particular focus on individual and collective behaviours in resource management with multiple decision makers.In our case study, the model was used as a platform for modelling multi-agent organizations, in order to support collective decision-making in water management. The model is capable of representing a distributed complex water management system, where simulated behaviours are based on field observations and on the participation of stakeholders. What is more, the multi–agent system approach enables the interaction and allows to formalize theIrene Pluchinotta – “Multi-Agent Modelling For Distributed Intelligent Decision In Water Management”iibehaviours of water users in the management process. A system dynamics modelling in an environment of interacting decision agents, allows us to explicitly consider the different frames and to simulate interactions when adopting a new policy. The model can showcase how the limited understanding of the interaction space affects the actions followed by each decision-makers and, finally, how it could lead to policy resistance mechanisms. In conclusion, the result is the richest possible picture of the existing problem situation that deals with irrigation water management in agricultural systems
Mejri, Hinda. "Un système d’aide à la régulation d’un réseau de transport multimodal perturbé : réponse au problème de congestion." Thesis, Ecole centrale de Lille, 2012. http://www.theses.fr/2012ECLI0008/document.
Full textTransport networks have been amplified by the increasing number of vehicles and stations and the emergence of new concepts essentially multimodal and intermodal. Thus, the task of managing public transport systems has become very complex and difficult for regulators.To cope with these difficulties, there is the development of systems decision support as an effective solution to traffic control. They can transmit real-time traffic information on transport networks. Our work is based on designing a control system of multimodal transport networks. It may be as an essential tool for effective solutions and real-time to the problem of traffic congestion. It can provide the necessary information to the user in making its decision to move with or without his car. The proposed system is a hybrid between a graph modeling the network and a multi-agent system. This will be supported by an evolutionary approach for generating an optimal control solution. This is justified by the open, distributed and complex network of multimodal transport