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Multi-robot systems (MRS) have gained interest as a versatile paradigm for complex task execution across various domains such as healthcare, logistics, and maintenance. Often, they are called to operate in variable and dynamic environments, which makes uncertainties arise and affect those systems. Uncertainties require the system to be able to adapt its behavior at runtime, in response to the changing and unpredictable conditions in its operating environment. Moreover, often the behavior of the robots cannot be completely anticipated at design time. Consequently, static mission planning is not always suitable: mission specifications need to take into account the uncertainties and, hence, be dynamic and re-configurable at runtime, when the required knowledge is available.
Filippone et al. (Mon,) studied this question.