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This thesis is exploratory research of an environment-driven evolutionary system.
This evolution- ary system is a system where the fitness of an individual is not
calculated by a fitness function, but evolution is driven by environmental
properties. Not much is known about environment- driven evolutionary algorithms
and their effect on the morphological complexity of individuals wandering around
in them. The performance and complexity of soft-bodied robots in large populations in an environment-driven evolutionary system is investigated in different
environments. Multiple measures of morphological complexity are proposed to
study it over the course of the experiments. These large populations are simulated
in parallel using the VoxCAD simulator. To create additional environments and
possibly multiple equilibria, two mechanisms have been introduced to change the
evolutionary landscape of the pedestrians. We have found that under all conditions
the distance that the robots move increases over time. We also have found that, for
the small timeframe that the robots have been simulated, the morphological
complexity does not necessarily grow over time. This contradicts previous work.