While Thomas Kuhn's theory of scientific revolutions does not specifically deal with validation, the validation of simulations can be related in various ways to Kuhn's theory: 1) Computer simulations are sometimes depicted as located between experiments and theoretical reasoning, thus potentially blurring the line between theory and empirical research. Does this require a new kind of research logic that is different from the classical paradigm which clearly distinguishes between theory and empirical observation? I argue that this is not the case. 2) Another typical feature of computer simulations is their being "motley" (Winsberg, 2003) with respect to the various premises that enter into simulations. A possible consequence is that in case of failure it can become difficult to tell which of the premises is to blame. Could this issue be understood as fostering Kuhn's mild relativism with respect to theory choice? I argue that there is no need to worry about relativism with respect to computer simulations, in particular.3) The field of social simulations, in particular, still lacks a common understanding concerning the requirements of empirical validation of simulations. Does this mean that social simulations are still in a pre-scientific state in the sense of Kuhn? My conclusion is that despite ongoing efforts to promote quality standards in this field, lack of proper validation is still a problem of many published simulation studies and that, at least large parts of social simulations must be considered as pre-scientific.

In a recent Philosophy of Science article, Gerhard Schurz proposes meta-inductivistic prediction strategies as a new approach to Hume's problem. This discussion examines the limitations of Schurz's approach. It can be proved that the meta-inductivistic approach does not work anymore if meta-inductivists have to face an infinite number of alternative predictors. With this limitation it remains doubtful whether the meta-inductivist can provide a full solution to the problem of induction.

This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. In order to justify this allegation I rely mostly but not entirely on the survey by Heath, Hill and Ciarallo (2009) according to which 2/3 of all agent-based-simulations are not properly empirically validated. In order to understand the reasons why so many social simulations are of questionable epistemic value, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling's neighborhood segregation model (Schelling, 1971) and Axelrod's reiterated Prisoner's Dilemma simulations of the evolution of cooperation (Axelrod, 1984). It is argued that Schelling's simulation is useful, because it can be related to empirical reality, while Axelrod's simulations and those of his followers cannot be related to empirical reality and therefore their scientific value remains doubtful. Finally, I critically discuss some of the typical epistemological background beliefs of modelers as expressed in Joshua Epsteins's keynote address "Why model?" (Epstein, 2008). Underestimating the importance of empirical validation is identified as one major cause of failure for social simulations.

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Backward induction as an evolutionary process. .. .. 8.7 The simulation software and the full simulation results on DVD.