Decision support system in health care building design based on case-based reasoning and reinforcement learning

Abstract

The health care building designing is a very difficult process in which there are a great quantity of parameters and variables that it is necessary to consider. The health care building should reach the population needs. Additionally, the design of this type of building and the related facilities involves a great quantity of regulations which they are adapted to the different countries. Thus, the health care facilities should be designed according to numerous and complex regulations. The checking of this regulation is very difficult and usually involves big teams of specialized engineers and architects. The proposed Case-Based Reasoning (CBR) and Reinforcement Learning can analyse the data about building design (provided in an Extended Mark-up Language or XML file, and other compatible formats), checking, and validating the regulations. This approach allows to reduce the specialized and high qualified personnel, providing a report with the checking regulations, and the traceability of warning and faults in the application of regulations.