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Agent-based models tend to be more and more complex. In order to cope with this increase of complexity, powerful modeling and simulation tools are required. These last years have seen the development of several platforms dedicated to the development of agent-based models. While some of them are still limited to the development of simple models, others allow(More)
Two types of model, equation-based models (EBMs) and agent-based models (ABMs) are now widely used in modeling ecological complex systems and seem not to be reconciled. While ABMs can help in exploring and explaining the local causes of global phenomena, EBMs are useful for predicting their long-term evolution without having to explore them through(More)
In this paper we present a method to improve and to update the knowledge used for the automation of the generalization of buildings based on agent paradigm. We propose to store 1/ each building decision, 2/ the reason why the decision was taken (the conflicts) 3/ the result of each algorithm (an improvement or not) and 4/ the successful process chain within(More)
Agent-based models are helpful to investigate complex dynamics in coupled humanenatural systems. However, model assessment, model comparison and replication are hampered to a large extent by a lack of transparency and comprehensibility in model descriptions. In this article we address the question of whether an ideal standard for describing models exists.(More)
Agent-based models are now used in numerous application domains (ecology, social sciences, etc.) but their use is still impeded by the lack of generic yet ready-to-use tools supporting the design and the simulation of complex models integrating multiple level of agency and realistic environments. The GAMA modeling and simulation platform is proposed to(More)
Agent-based simulations are now widely used to study complex systems. However, the problem of the agent design is still an open issue, especially for social-ecological models, where some of the agents represent human beings. In fact, designing complex agents able to act in a believable way is a difficult task, in particular when their behaviour is led by(More)
The global climate change induces an increase, in terms of frequency and devastating power, of natural disasters (particularly in developing countries). For facing this, there is a growing need for robotic assistance, for collecting information, managing disaster situation, rescuing victims and preserve human lives. It is one of the means recommended by the(More)
Many real world problems can be expressed as optimisation problems. Solving such problems means to find, among all possible solutions, the one that maximises an evaluation function. One approach to solve it is to use an informed search strategy. The principle of this kind of strategy is to use problem-specific knowledge beyond the definition of the problem(More)
—Both humans and artificial systems frequently use trial and error methods to problem solving. In order to be effective, this type of strategy implies having high quality control knowledge to guide the quest for the optimal solution. Unfortunately, this control knowledge is rarely perfect. Moreover, in artificial systems-as in humans-self-evaluation of(More)