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For two decades, multi-agent systems have been an attractive approach for problem solving and have been applied to a wide range of applications. Despite the lack of generic methodology, the reactive approach is interesting considering the properties it provides. This article presents a problem-solving model based on a swarm approach where agents interact using physics-inspired mechanisms. The initial problem and its constraints are represented through agents' environment, the dynamics of which is part of the problem-solving process. This model is then applied to localization and target tracking. Experiments assess our approach and compare it to widely-used classical algorithms.