Dynamic Distribution of Tasks in Health-Care Scenarios

Abstract

This paper presents a multiagent system that use an autonomous deliberative case-based reasoningagent to design an efficient working day. The system has been developed to plan and distribute tasks in a health care scenario, specifically in geriatric residences. This model generates a planning of tasks, minimizing the resources necessary for its accomplishment and obtaining the maximum benefits. 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.