[en] An agent (animal or robot) is said to exhibit opportunistic behaviours, when it can identify favourable circumstances for its actions, even when the environment is non-optimal (i.e. when the stimuli encountered are a priori weakly incentive). In animals, there is evidence that the stronger their motivation for a task, the more they tend to accept as relevant those stimuli to which they previously paid no attention. It is shown how motivations and their reactivity threshold bring about perceptual generalizations that might help animals to recognize more opportunities to act. This process is likely to be useful in uncertain environments, such as the real world. Designers interested in autonomous mobile robots construct machines with flexible goal achievements. In particular, these robots are provided with specific motivational states that determine when to carry out a given task. However, it is argued here that these motivational states do not allow robots to recognize opportunities to act because, contrary to the case with animals, artificial motivational systems are not designed to deal with non-optimality of the environment.