comparison toolboxes/FullBNT-1.0.7/HMM/pomdp_sample.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [obs, hidden] = pomdp_sample(initial_prob, transmat, obsmat, act)
+% SAMPLE_POMDP Generate a random sequence from a Partially Observed Markov Decision Process.
+% [obs, hidden] = sample_pomdp(prior, transmat, obsmat, act)
+%
+% Inputs:
+% prior(i) = Pr(Q(1)=i)
+% transmat{a}(i,j) = Pr(Q(t)=j | Q(t-1)=i, A(t)=a)
+% obsmat(i,k) = Pr(Y(t)=k | Q(t)=i)
+% act(a) = A(t), so act(1) is ignored
+%
+% Output:
+% obs and hidden are vectors of length T=length(act)
+
+
+len = length(act);
+hidden = mdp_sample(initial_prob, transmat, act);
+obs = zeros(1, len);
+for t=1:len
+  obs(t) = sample_discrete(obsmat(hidden(t),:));
+end