NK Simulation Modeling

This chapter discusses NK simulation modelling, which have been launched and developed primarily by Kauffman from the end of sixties, as a candidate for capturing networks dynamics. Grounded in reference to biological networks, it has aroused a grate and durable interest in economics and management sciences too. This methodology is split into a version focused on studying Boolean networks dynamics, whose trajectories are substantially conditioned by Boolean functions, and a version focused on systems co-evolutionary paths, driven by the search for optimizing its fitness value. Besides the unquestionable value of Kauffman’s work for the theoretical implications on evolutionary biology, in this chapter failures and limitations of both NK modelling versions are discussed. In particular, it is shown that, as applications try to be more realistic, this modelling becomes hardly treatable from a computational point of view. On the other hand, especially the fitness landscape version is very useful to show general aspects of system’s dynamics, and the impossibility to find general optima (excepted for very special and unrealistic cases).

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