Fujitsu, Fujitsu Laboratories and the Fujitsu Social Mathematics Division of the Institute of Mathematics for Industry at Kyushu University say they have developed an AI-based matching technology that uses game theory to automatically calculate an optimal matching of children to daycare centers.
Using this technology, a complicated daycare admissions screening that had previously required several days by hand took only seconds.
The admissions process of matching children to daycare centers seeks to fulfill as many of the applicants’ preferences as possible based on complex requirements, including applicant priority criteria set by each local government and requests for siblings to be admitted to the same daycare center. This has made it difficult to automate the matching process in a way that would satisfy all applicants. As a result, many local governments have, until now, manually conducted trial and error to as much as possible accommodate preferences for siblings to attend the same daycare center, but this meant that seat assignment by the local government could take several weeks, requiring some time before the applicants could be notified of the results. There were also issues such as siblings being admitted to different daycare centers due to applicant preferences not being accepted.
Now, Fujitsu says its newly developed AI technology makes it possible to match children to daycare centers, meeting as many preferences as possible, following a priority ranking.
This is done by modeling the dependency relationships of complex requirements, including parents who prioritize siblings going to the same daycare center, or parents who do not mind if their children go to different daycare centers as long as both children get a seat, using a mathematical model based on game theory, which rationally resolves the relationships between people having differing values.
Game theory, which is used to create the model in this technology, is a mathematical approach that rationally handles conflicts and cooperation between people in society where interests are not necessarily aligned. Mathematical research based on the game theory is primarily ongoing in the field of economics. By applying this theory to the matching problem of daycare admissions, AI technology successfully finds the optimal assignment pattern that prioritizes applicants having the highest priority, even in cases of multiple patterns that fulfill all rules, or no patterns fulfill all rules.
The AI technology was evaluated using anonymized data for about 8,000 children in Saitama. The technology was tasked to calculate optimal seat assignments that fulfilled the complex and detailed requirements unique to Saitama in just seconds. The current process takes 20 to 30 people quite a few days to complete. The AI matching technology completed the entire process in a few seconds.
When this technology is commercialized, Fujitsu said, it is expected that it will not only dramatically reduce the burden of seat assignment tasks on local government personnel, it will also enable decision notifications to be sent to applicants earlier, improving services to residents. Moreover, it could enable the process to incorporate more detailed requirements without increasing the amount of work or the chance of overlooking something, improving applicant satisfaction.
Fujitsu plans to offer this technology as an optional service for MICJET MISALIO Child-Rearing Support, a childcare support system for local governments, during fiscal 2017. The company will also work to apply this technology to a variety of matching problems as part of “Human Centric AI Zinrai”, Fujitsu’s proprietary artificial intelligence technology.