Description
Processes of multilevel organisational learning emerge as a cyclic interplay of various mechanisms at different levels. To analyse and simulate them computationally, the self-modeling network modelling approach from AI provides a powerful means to address the complexity of the interaction of different adaptation mechanisms and the control over them. In this keynote speech, recent developments are presented showing how this approach can be used to analyse and simulate complex processes of multilevel organisational learning. This covers both feed-forward learning to learn shared team or organisation mental models out of individually learned personal mental models and feedback learning to let individuals learn personal mental models from shared mental models. It is shown how by a self-modeling network, the different types of learning can be modeled using a first-order self-model for the learning and a second-order self-model level for the control over the learning. It will be discussed how this may be applied in the context of improving safety in health-related organisations such as hospitals.| Period | 14 Oct 2022 → 16 Oct 2022 |
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| Event title | The Second International Joint Conference on Robotics and Artificial Intelligence, JCRAI'22 |
| Event type | Conference |
| Location | Chengdu, ChinaShow on map |
| Degree of Recognition | International |