Claus Beisbart

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

In physics, objects are often assigned vector characteristics such as a specific velocity. How can this be understood from a metaphysical point of view – is assigning an object a vector characteristic to attribute it an intrinsic property? As a short review of Newtonian, special relativistic and general relativistic physics shows, if we wish to assign some object a vector characteristic, we have to relate it to something – call it S. If S is to be different from the original object – and I argue for this assumption – then having the specific vector characteristic is not an intrinsic property under different readings of “intrinsic”. For instance, I argue that lonely objects with different orientations do not constitute metaphysically distinct possibilities. There are, however, difficulties in applying the loneliness test, and they concern the role of the space‐time