  In this thesis I present a virtual laboratory which implements five different
models for controlling animats: a rule-based system, a behaviour-based system,
a concept-based system, a neural network, and a Braitenberg architecture.
Through different experiments, I compare the performance of the models and
conclude that there is no "best" model, since different models are better for
different things in different contexts.
  The models I chose, although quite simple, represent different approaches for
studying cognition. Using the results as an empirical philosophical aid,
  I note that there is no "best" approach for studying cognition, since
different approaches have all advantages and disadvantages, because they study
different aspects of cognition from different contexts. This has implications
for current debates on "proper" approaches for cognition: all approaches are a
bit proper, but none will be "proper enough". I draw remarks on the notion of
cognition abstracting from all the approaches used to study it, and propose a
simple classification for different types of cognition.
