<:> Summary
- Markov models are useful for generative applications with all
types of sequential data.
- Structure modeled depends on the level of analysis applied.
- Generated instances will then show good structure only at the
relevant level.
- Hierarchical adapation of the process through derivation of
informationally optimal encodings (uncertainization).
- Mixed results.