first been established in economic theory. For example, the notions of utility functions and preferences that are central to many models and algorithms of autonomous agents and multi-agent systems stem from ideas of the philosophers and economists Jeremy Bentham and John Stuart Mill [@sen_1991]. Von Neumann’s and Morgenstern’s ground-breaking game theoretical work *Theory of Games and Economic Behavior* [@von2007theory] influenced generations of both economics and artificial intelligence researchers. More recently, the works of Daniel Kahneman and Richard Thaler, who both have received the Nobel Memorial Prize in Economic Sciences for their research on behavioral economics, have inspired new work on and discussions about ethics and responsibility in artificial intelligence [@Dignum:2018:EDN:3278721.3278745]. A key concept at the intersection of economics and artificial intelligence is the notion of economic rationality. In the same way that a rational economic decision-maker–traditionally a human agent–is ideally expected to act according to clear and consistent preferences [@rubinstein1998modeling p. 7 et sqq.], artificially intelligent agents should as stated in the definition of a rational agent by Russel and Norvig [@russell2016artificial p. 37]. The concept of economical rationality is reflected in many ground-breaking works on economics, such as the Nash equilibrium [@Nash48], and Tversky’s and Kahneman’s empirical work on 