  The implicit theory that a simulation represents is precisely not in the
individual choices but rather in the 'envelope' of possible trajectories - what
is important is the shape of the whole envelope. Typically a huge amount of
computation is required when experimenting with factors bearing on the dynamics
of a simulation to tease out what affects the shape of this envelope. In this
paper we present a methodology aimed at systematically exploring this envelope.
We propose a method for searching for tendencies and proving their necessity
relative to a range of parameterisations of the model and agents' choices, and
to the logic of the simulation language. The exploration consists of a forward
chaining generation of the trajectories associated to and constrained by such a
range of parameterisations and choices. Additionally, we propose a
computational procedure that helps implement this exploration by translating a
Multi Agent System simulation into a constraint-based search over possible
trajectories by 'compiling' the simulation rules into a more specific form,
namely by partitioning the simulation rules using appropriate modularity in the
simulation. An example of this procedure is exhibited.
  Keywords: Constraint Search, Constraint Logic Programming, Proof, Emergence,
Tendencies
