Resource allocation in home care services using reinforcement learning

This paper proposes an innovative method based on reinforcement learning techniques to optimally allocates home care resources in controlled urban environments. We demonstrate the value of this approach when compared with traditional allocation heuristics by simulating a real-life scenario in the city of Barcelona. Our results show that the proposed tool can help home care services accommodate the increase in demand by optimizing human and time resources through more effective planning. In the long term, this will improve the overall quality of this service and positively affect the well-being of the elderly.