Abstract
Manufacturing systems has been designed to be rational optimal under static situations. Resently however, situations surrounding manufacturing systems are becoming increasingly large-scale and uncertain, and structures of them are becoming complex. It is difficult to deal with such incomplete conditions using existing top-down methods. Self-organization-based Biological Manufacturing Systems (BMS) has flexibility and adaptivity under complex and uncertain situations. On the other hand, local competition occurs among agents, or the system is trapped in local solutions, mainly because the sum of local goals of agents is not equal to the system goal. This study proposes a design approach for self-organization-based BMS by introducing agents' bounded rationality, to generate effective solutions under incomplete conditions, through avoidance local competition without top-down control or additional information. This paper shows the results of simulations, which indicate the existence of differences between two types of bounded rationality, and that designing appropriate bounded-rational agents might be an effective approach to derive adaptive solutions.
