J.M. Corchado et al. (Eds.): Trends in PAAMS, AISC 90, pp. 51–58. springerlink.com © Springer-Verlag Berlin Heidelberg 2011 Dynamic Distribution of Tasks in Health-Care Scenarios Carolina Zato, Ana de Luis, and Juan F. De Paz * Abstract. This paper presents a multiagent system that use an autonomous delib- erative case-based reasoningagent to design an efficient working day. The system has been developed to plan and distribute tasks in a health care scenario, specifi- cally in geriatric residences. This model generates a planning of tasks, minimizing the resources necessary for its accomplishment and obtaining the maximum bene- fits.For this purpose, the queuing theory and genetic algorithms have been include in a CBRarchitecture to obtain an efficient distribution. To evaluate the model, the obtained results have been compared with a previous method of planning based on neural networks. Keywords: multiagent systems, queuing theory, genetic algorithm, task schedul- ing, health-care. 1 Introduction During the last three decades the number of Europeans over 60 years old has risen by about 50%. Today they represent more than 25% of the population and it is es- timated that in 20 years this percentage will rise to one third of the population, meaning 100 millions of citizens [1]. This situation is not exclusive to Europe, since studies in other parts of the world show similar tendencies. In the United States of America, people over 65 years old are the fastest growing segment of the population and it is expected that in 2020 they will represent about 1 of 6 citizens totalling 69 million by 2030. Furthermore, over 20% of people over 85 years old have a limited capacity for independent living, requiring continuous monitoring and daily care, for this reason it is important to create a task planner and control system for elderly people. Carolina Zato . Ana de Luis . Juan F. De Paz Department of Computer Science and Automation, University of Salamanca Plaza de la Merced, s/n, 37008, Salamanca, Spain e-mail: {carol_zato,adeluis,fcofds}@usal.es