Towards Learning Processes in a Resilient Human-Machine System

This paper addresses the topic of learning in resilient systems, and more especially human-machine systems. Resilient systems aim at managing the occurrence of perturbations by taking into consideration their past experiences, either successes or failures. Capitalizing the management of perturbations is an essential part of a resilient process. Three ways of learning are discussed in this paper: learning from successes and errors, learning from cooperation and learning from affordances. Human-machine cooperation and affordances are both considered from the point of view of successes and failures.