?? tabular_decision_node.m
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function CPD = tabular_decision_node(sz, CPT)
% TABULAR_DECISION_NODE Represent the randomized policy over a discrete decision/action node as a table
% CPD = tabular_decision_node(sz, CPT)
%
% sz(1:end-1) is the sizes of the parents, sz(end) is the size of this node
% By default, CPT is set to the uniform random 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');
return;
elseif isa(sz, 'tabular_decision_node')
% This might occur if we are copying an object.
CPD = sz;
return;
end
CPD = init_fields;
if nargin < 2
CPT = mk_stochastic(myones(sz));
else
CPT = myreshape(CPT, sz);
end
CPD.CPT = CPT;
CPD.size = sz;
CPD = class(CPD, 'tabular_decision_node');
%%%%%%%%%%%
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.size = [];
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