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Time critical task assignment problems are frequently found in operating systems and flight control applications. For instance, in a flight control real time application, one wrong task assignment decision could result in an airplane accident. To make things worse, these crucial decisions have to be taken in milliseconds. In order to address time critical task assignment problems, the Clustering Task Assignment Approach (CTA) is proposed. The idea is to cluster the groups into tasks with the best candidates(free agents) according to a heuristic. In other words, the place where agents needs to reach(task facility) is designed as a cluster centroid and the agents inside each cluster are the candidates to execute each task. Agents compete with each other by means of an objective function in order to define the assigned task. The algorithm is compared against the well known Contract Net Protocol(CNET) and outperform it in terms of speed reducing the number of calls to the score function in 400%, the solution quality is 28% better as well. This algorithm was designed to work with time critical applications in which agents have to move from one place to another.

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I hold a Bachelors degree in Computer Science. I did an internship as a Java Developer at the GIS deparment of Belo Horizonte City Hall for 2 years. I worked for 8 months at Capgemini. Later I worked for 4 months as IOS developer in Canada, and then I went to Germany for an IOS development internship. I hold a Master in AI that took place in Madrid

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