 Quote by FlufferNuterFSU
A stochastic process is a process in which some later state is determined by predictable actions and by a random element.
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In a way, yes. The "actions" are implicit in the underlying event space and dependency structures. In general definition of a stochastic process as a set of random variables indexed by an ordered set, the predictable part would come from our knowledge of the dependency structure and the particular sample path; the random part would be everything else we don't know about the sample path.
 Quote by FlufferNuterFSU
this "random element" is this meant to compensate for unknown (non-predictable) actions or is this just a random factor for some other purpose?
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Yes - it depends on how the underlying event space is formulated. Take a coin toss as an example, where [tex]X_t=X_0[/tex] for t>0 and [tex]X_0[/tex] is a random variable that maps events to either 0 or 1. The underlying event space could be just the 2 events Heads or Tails, or it could be a description of the entire universe leading up to the point in time of the coin toss. The former model summarizes the uncertainties of the latter.
Hope this helps.