Monte Carlo experiments may include assumptions such as the distribution, mean, median etc, but its not necessary. However, the very fact that the user decides whether to include assumptions and constraints or not doesn't this makes it a deterministic environment?
For example, if I decide to follow a stochastic process, then I already know that the outcome will be random. I'm not aware of the outcome itself, but taking no assumptions is already an assumption.
Therefore even if the process is stochastic it does not undo that the process itself is a "laboratory event". The most famous example of a stochastic process is the dice throwing. Given a formula to do a simulation, it inevitably be incomplete and it will not describe any possible case, such as different levels of gravity, any possible terrain, the case of walls, dice materials and structural problems, therefore we are forced to put constraints in order to construct our "laboratory".
Could you clarify me these definitions and explain me whether my point of view is true or false?