Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : September 15, 2021 - September 17, 2021
The Real World is changing rapidly and extensively. Yesterday, changes were smooth, so we could differentiate them and predict the future. But today changes are sharp, so we cannot predict the future. Yesterday our world was closed with boundary, but today it is an open world. Thus, yesterday we could apply mathematical approaches in a straightforward manner in a Euclidean Space, which requires datasets to be orthonormal and cardinal scale based with units. But we cannot satisfy these requirements today. The Real World becomes too much complicated, and datasets are now composed of wide varieties of information. Therefore, traditional Euclidean Space approaches do not work anymore. Furthermore, materials are getting softer and softer. Until now, objects were hard, so we could easily understand how we should handle them, with vision alone, even from a distance. But with the remarkable progress of material engineering, objects are getting softer and we need to directly interact with them to find out how we should deal with them. In short, we have been paying efforts to solve the problem, with the goal fixed from the first. It was tactics. But now to cope with the rapidly and unpredictably changing the Real World, we need to find the goal. Strategic decision making becomes important. And although mind accommodates body and brain, it is the body that directly interact with the Real World. And the brain processes these accumulated pieces of past experiences. Thus, mind, or to put it short, instinct becomes crucially important. Mahalanobis Distance-Pattern (MDP) Approach is proposed as a new Non-Euclidean Space approach to tackle the problems which cannot be solved with the traditional Euclidean Space approaches. The uniqueness of MDP is Ordinal number based and pattern is used for nonverbal communication.
