Computation in Complex Environments

This contribution for Computational Intelligence in Expensive Optimization Problems aims to draw attention to the complexity of environments as an integral part of optimization. Railway timetable problems are introduced as an example of a complex environment, and so-called symbiotic networks will be discussed in greater detail as a novel way of optimization of complex environments through computational intelligence. Putinanotherway,organizedcomplexitymovesawayfromtraditional machines, whichhavesupremeperformancefortheirintendedtasks,butalsorequireverysta- bleandpredictableenvironments.Ratheralineisdrawntowardslivingorganisms, whichareveryrobustandarebetteradjustedforcontingentenvironmentsthanma- chinesare.Alongthisgradient,‘robustmachines’formaninterestingfieldofin- quiryforoptimizationproblems.RailwayTimetableProblems(RTP)canbeseenas abenchmarkforsuchrobustmachines(oralgorithms). Thesecondconcept,‘symbioticnetworks’,isintroducedasanoptimizationstrat- egythatcan,tosomeextent,optimizeinsuchcomplexenvironments.RTPhasbeen