  We start by an introduction to the basic concepts of computability theory and
the introduction of the concept of Turing machine and computation universality.
Then se turn to the exploration of trade-offs between different measures of
complexity, particularly algorithmic (program-size) and computational (time)
complexity as a mean to explain these measure in a novel manner. The
investigation proceeds by an exhaustive exploration and systematic study of the
functions computed by a large set of small Turing machines with 2 and 3 states
with particular attention to runtimes, space-usages and patterns corresponding
to the computed functions when the machines have access to larger resources
(more states).
  We report that the average runtime of Turing machines computing a function
increases as a function of the number of states, indicating that non-trivial
machines tend to occupy all the resources at hand. General slow-down was
witnessed and some incidental cases of (linear) speed-up were found. Throughout
our study various interesting structures were encountered. We unveil a study of
structures in the micro-cosmos of small Turing machines.
