I'm quite new to LW, and find myself wondering whether Hidden Markov models (HMM) are underappreciated as a formal reasoning tool in the rationalist community, especially compared to Bayesian networks?
Perhaps it's because HMM seem to be more difficult to grasp?
Or it's because formally HMM are just a special case of Bayesian networks (i.e. dynamic Bayes nets)? Still, HMM are widely used in science on their own.
For comparison, Google search "bayes OR bayesian network OR net" site:lesswrong.com gives 1,090 results.
Google search hidden markov model site:lesswrong.com gives 91 results.
Out of curiosity, did you happen to read Kurzweil's recent book on HHMMs?
I think the safest answer is that a HMM is just a specific way of mathematically writing down an updating Bayesian network.