1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
|
function CPD = tabular_decision_node(bnet, self, CPT)
% TABULAR_DECISION_NODE Represent a stochastic policy over a discrete decision/action node as a table
% CPD = tabular_decision_node(bnet, self, CPT)
%
% node is the number of a node in this equivalence class.
% CPT is an optional argument (see tabular_CPD for details); by default, it is the uniform policy.
if nargin==0
% This occurs if we are trying to load an object from a file.
CPD = init_fields;
CPD = class(CPD, 'tabular_decision_node', discrete_CPD(1, []));
return;
elseif isa(bnet, 'tabular_decision_node')
% This might occur if we are copying an object.
CPD = bnet;
return;
end
CPD = init_fields;
ns = bnet.node_sizes;
fam = family(bnet.dag, self);
ps = parents(bnet.dag, self);
sz = ns(fam);
if nargin < 3
CPT = mk_stochastic(myones(sz));
else
CPT = myreshape(CPT, sz);
end
CPD.CPT = CPT;
CPD.sizes = sz;
clamped = 1; % don't update using EM
CPD = class(CPD, 'tabular_decision_node', discrete_CPD(clamped, ns([ps self])));
%%%%%%%%%%%
function CPD = init_fields()
% This ensures we define the fields in the same order
% no matter whether we load an object from a file,
% or create it from scratch. (Matlab requires this.)
CPD.CPT = [];
CPD.sizes = [];
|
