wolffd@0: function CPD = tabular_decision_node(sz, CPT)
wolffd@0: % TABULAR_DECISION_NODE Represent the randomized policy over a discrete decision/action node as a table
wolffd@0: % CPD = tabular_decision_node(sz, CPT)
wolffd@0: %
wolffd@0: % sz(1:end-1) is the sizes of the parents, sz(end) is the size of this node
wolffd@0: % By default, CPT is set to the uniform random policy
wolffd@0: 
wolffd@0: if nargin==0
wolffd@0:   % This occurs if we are trying to load an object from a file.
wolffd@0:   CPD = init_fields;
wolffd@0:   CPD = class(CPD, 'tabular_decision_node');
wolffd@0:   return;
wolffd@0: elseif isa(sz, 'tabular_decision_node')
wolffd@0:   % This might occur if we are copying an object.
wolffd@0:   CPD = sz;
wolffd@0:   return;
wolffd@0: end
wolffd@0: CPD = init_fields;
wolffd@0: 
wolffd@0: if nargin < 2
wolffd@0:   CPT = mk_stochastic(myones(sz)); 
wolffd@0: else
wolffd@0:   CPT = myreshape(CPT, sz);
wolffd@0: end
wolffd@0: 
wolffd@0: CPD.CPT = CPT;
wolffd@0: CPD.size = sz;
wolffd@0: 
wolffd@0: CPD = class(CPD, 'tabular_decision_node');
wolffd@0: 
wolffd@0: %%%%%%%%%%%
wolffd@0: 
wolffd@0: function CPD = init_fields()
wolffd@0: % This ensures we define the fields in the same order 
wolffd@0: % no matter whether we load an object from a file,
wolffd@0: % or create it from scratch. (Matlab requires this.)
wolffd@0: 
wolffd@0: CPD.CPT = [];
wolffd@0: CPD.size = [];