This article presents the methodological background and an overview of recent applications of artificial autonomous decision systems (AADS), endowed with intelligent coordination algorithms. The research results comprise modelling the decision-making processes in autonomous anticipatory systems, specifically the decisions made in teams composed of robots and humans. These can be modelled as timed anticipatory networks. We present selected real-life applications of anticipatory decision support methods, such as industrial safety management systems and coordination of ground unmanned autonomous robot teams. New algorithms have been proposed to solve multicriteria combinatorial optimization problems that occur when selecting safety strategies, such as AADS evacuation from endangered areas. Decision analytics, based on reference sets, is proposed to solve optimal supervisory control problems related to coordinated autonomous robot deployment. Finally, we discuss the scenarios of future research on AADS and their applications in developing decision algorithms for teams of autonomous harvesting robots or robotic inspection of large industrial plants.