  Creatures in the real world constantly encounter new and diverse challenges
they have never seen before. They will often need to adapt to some of these
tasks and solve them in order to survive. This almost endless world of novel
challenges is not as common in virtual environments, where artificially
evolving agents often have a limited set of tasks to solve. An exception to
this is the field of open-endedness where the goal is to create unbounded
exploration of interesting artefacts. We want to move one step closer to
creating simulated environments similar to the diverse real world, where agents
can both find solvable tasks, and adapt to them. Through the use of MAP-Elites
we create a structured repertoire, a map, of terrains and virtual creatures
that locomote through them. By using novelty as a dimension in the grid, the
map can continuously develop to encourage exploration of new environments. The
agents must adapt to the environments found, but can also search for
environments within each cell of the grid to find the one that best fits their
set of skills. Our approach combines the structure of MAP-Elites, which can
allow the virtual creatures to use adjacent cells as stepping stones to solve
increasingly difficult environments, with open-ended innovation. This leads to
a search that is unbounded, but still has a clear structure. We find that while
handcrafted bounded dimensions for the map lead to quicker exploration of a
large set of environments, both the bounded and unbounded approach manage to
solve a diverse set of terrains.
