We discuss human collaborative discovery processes using a production system model as a cognitive simulator. We have developed an interactive production system architecture to construct the simulator. Two production systems interactively find targets in which the only experimental results are shared; each does not know the hypothesis the other system has. Through this kind of interaction, we verify whether or not the performance of two systems interactively finding targets exceeds that of two systems independently finding targets. If we confirm the superiority of collaborative discovery, we approve of emergence by the interaction. The results are: (1) generally speaking collaboration does not produces the emergence defined above, and (2) as the different degree of hypothesis testing strategies that the two system use gets larger, the benefits of interaction gradually increases.

This study investigated the relationship between human use of automation and their sensitivity to changes in automation and manual performance. In the real world, automation and manual performance change dynamically with changes in the environment. However, a few studies investigated whether changes in automation or manual performance have more effect on whether users choose to use automation. We used two types of experimental tracking tasks in which the participants had to select whether to use automation or conduct manual operation while monitoring the variable performance of automation and manual operation. As a result, we found that there is a mutual relationship between human use of automation and their sensitivity to automation and manual performance changes. Also, users do not react equally to both automation and manual performance changes although they use automation adequately.