% oil wildcatter influence diagram in Cowell et al p172 T = 1; UT = 2; O = 3; R = 4; D = 5; UD = 6; N = 6; dag = zeros(N); dag(T, [UT R D]) = 1; dag(O, [R UD]) = 1; dag(R, D) = 1; dag(D, UD) = 1; ns = zeros(1,N); ns(O) = 3; ns(R) = 4; ns(T) = 2; ns(D) = 2; ns(UT) = 1; ns(UD) = 1; limid = mk_limid(dag, ns, 'chance', [O R], 'decision', [T D], 'utility', [UT UD]); limid.CPD{O} = tabular_CPD(limid, O, [0.5 0.3 0.2]); tbl = [0.6 0 0.3 0 0.1 0 0.3 0 0.4 0 0.4 0 0.1 0 0.3 0 0.5 0 0 1 0 1 0 1]; limid.CPD{R} = tabular_CPD(limid, R, tbl); limid.CPD{UT} = tabular_utility_node(limid, UT, [-10 0]); limid.CPD{UD} = tabular_utility_node(limid, UD, [-70 50 200 0 0 0]); if 1 % start with uniform policies limid.CPD{T} = tabular_decision_node(limid, T); limid.CPD{D} = tabular_decision_node(limid, D); else % hard code optimal policies limid.CPD{T} = tabular_decision_node(limid, T, [1.0 0.0]); a = 0.5; b = 1-a; % arbitrary value tbl = myreshape([0 a 1 a 1 a a a 1 b 0 b 0 b b b], ns([T R D])); limid.CPD{D} = tabular_decision_node(limid, D, tbl); end fname = '/home/cs/murphyk/matlab/Misc/loopybel.txt'; engines = {}; engines{end+1} = global_joint_inf_engine(limid); engines{end+1} = jtree_limid_inf_engine(limid); %engines{end+1} = belprop_inf_engine(limid, 'max_iter', 3*N, 'filename', fname); exact = [1 2]; %approx = 3; approx = []; E = length(engines); strategy = cell(1, E); MEU = zeros(1, E); for e=1:E [strategy{e}, MEU(e)] = solve_limid(engines{e}); MEU end MEU for e=exact(:)' assert(approxeq(MEU(e), 22.5)) assert(argmax(strategy{e}{T} == 1)); % test = yes t = 1; % test = yes for r=[2 3] % OpS, ClS assert(argmax(squeeze(strategy{e}{D}(t,r,:))) == 1); % drill = yes end r = 1; % noS assert(argmax(squeeze(strategy{e}{D}(t,r,:))) == 2); % drill = no end for e=approx(:)' approxeq(strategy{exact(1)}{T}, strategy{e}{T}) approxeq(strategy{exact(1)}{D}, strategy{e}{D}) end
