Evolutionary algorithms solve a problem by maintaining a population of variant partial solutions and applying recombination operators to them. Those operators can be considered valid, or available operations in a space of configurations. Our brick structures algorithms are solving problems of spatial arrangement, subject to buildability restrictions, starting from a known initial configuration and advancing, one step at a time, by legal transformations. The simulation enforces that each step is physically correct.
The implication is that the succession of genetic transformations that yield to a final stage can be considered a plan. Problems of planning for spatial arrangement are classic in AI . One plausible future application of structural evolutionary algorithms is to adapt the recombination operations to reflect valid reconfigurations of a modular metamorphic robot. Problems of robot locomotion for example could be solved by evolving a plan for the desired final configuration from the starting one.
We ran an exploratory experiment which evolves an imaginary amoeba-like creature
made of Lego bricks (fig. 2.35). Once a goal state is obtained,
the ``family tree'' from the initial to final configurations represents a sequence
of valid transformations.
The mutation operations are interpreted as the ``valid actions'' of the creature (i.e., extending, retracting or displacing limbs) and recombinations amount to macro operators, chaining a sequence of actions.