Local search heuristics: Fitness Cloud versus Fitness Landscape
  This paper introduces the concept of fitness cloud as an alternative way to
visualize and analyze search spaces than given by the geographic notion of
fitness landscape. It is argued that the fitness cloud concept overcomes
several deficiencies of the landscape representation. Our analysis is based on
the correlation between fitness of solutions and fitnesses of nearest solutions
according to some neighboring. We focus on the behavior of local search
heuristics, such as hill climber, on the well-known NK fitness landscape. In
both cases the fitness vs. fitness correlation is shown to be related to the
epistatic parameter K.
