|
wolffd@0
|
1 % oil wildcatter influence diagram in Cowell et al p172
|
|
wolffd@0
|
2
|
|
wolffd@0
|
3 % T = test for oil?
|
|
wolffd@0
|
4 % UT = utility (negative cost) of testing
|
|
wolffd@0
|
5 % O = amount of oil = Dry, Wet or Soaking
|
|
wolffd@0
|
6 % R = results of test = NoStrucure, OpenStructure, ClosedStructure or NoResult
|
|
wolffd@0
|
7 % D = drill?
|
|
wolffd@0
|
8 % UD = utility of drilling
|
|
wolffd@0
|
9
|
|
wolffd@0
|
10 % Decision sequence = T R D O
|
|
wolffd@0
|
11
|
|
wolffd@0
|
12 T = 1; UT = 2; O = 3; R = 4; D = 5; UD = 6;
|
|
wolffd@0
|
13 N = 6;
|
|
wolffd@0
|
14 dag = zeros(N);
|
|
wolffd@0
|
15 dag(T, [UT R D]) = 1;
|
|
wolffd@0
|
16 dag(O, [R UD]) = 1;
|
|
wolffd@0
|
17 dag(R, D) = 1;
|
|
wolffd@0
|
18 dag(D, UD) = 1;
|
|
wolffd@0
|
19
|
|
wolffd@0
|
20 ns = zeros(1,N);
|
|
wolffd@0
|
21 ns(O) = 3; ns(R) = 4; ns(T) = 2; ns(D) = 2; ns(UT) = 1; ns(UD) = 1;
|
|
wolffd@0
|
22
|
|
wolffd@0
|
23 limid = mk_limid(dag, ns, 'chance', [O R], 'decision', [T D], 'utility', [UT UD]);
|
|
wolffd@0
|
24
|
|
wolffd@0
|
25 limid.CPD{O} = tabular_CPD(limid, O, [0.5 0.3 0.2]);
|
|
wolffd@0
|
26 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];
|
|
wolffd@0
|
27 limid.CPD{R} = tabular_CPD(limid, R, tbl);
|
|
wolffd@0
|
28
|
|
wolffd@0
|
29 limid.CPD{UT} = tabular_utility_node(limid, UT, [-10 0]);
|
|
wolffd@0
|
30 limid.CPD{UD} = tabular_utility_node(limid, UD, [-70 50 200 0 0 0]);
|
|
wolffd@0
|
31
|
|
wolffd@0
|
32 if 1
|
|
wolffd@0
|
33 % start with uniform policies
|
|
wolffd@0
|
34 limid.CPD{T} = tabular_decision_node(limid, T);
|
|
wolffd@0
|
35 limid.CPD{D} = tabular_decision_node(limid, D);
|
|
wolffd@0
|
36 else
|
|
wolffd@0
|
37 % hard code optimal policies
|
|
wolffd@0
|
38 limid.CPD{T} = tabular_decision_node(limid, T, [1.0 0.0]);
|
|
wolffd@0
|
39 a = 0.5; b = 1-a; % arbitrary value
|
|
wolffd@0
|
40 tbl = myreshape([0 a 1 a 1 a a a 1 b 0 b 0 b b b], ns([T R D]));
|
|
wolffd@0
|
41 limid.CPD{D} = tabular_decision_node(limid, D, tbl);
|
|
wolffd@0
|
42 end
|
|
wolffd@0
|
43
|
|
wolffd@0
|
44 %fname = '/home/cs/murphyk/matlab/Misc/loopybel.txt';
|
|
wolffd@0
|
45
|
|
wolffd@0
|
46 engines = {};
|
|
wolffd@0
|
47 engines{end+1} = global_joint_inf_engine(limid);
|
|
wolffd@0
|
48 engines{end+1} = jtree_limid_inf_engine(limid);
|
|
wolffd@0
|
49 %engines{end+1} = belprop_inf_engine(limid, 'max_iter', 3*N, 'filename', fname);
|
|
wolffd@0
|
50
|
|
wolffd@0
|
51 exact = [1 2];
|
|
wolffd@0
|
52 %approx = 3;
|
|
wolffd@0
|
53 approx = [];
|
|
wolffd@0
|
54
|
|
wolffd@0
|
55 E = length(engines);
|
|
wolffd@0
|
56 strategy = cell(1, E);
|
|
wolffd@0
|
57 MEU = zeros(1, E);
|
|
wolffd@0
|
58 for e=1:E
|
|
wolffd@0
|
59 [strategy{e}, MEU(e)] = solve_limid(engines{e});
|
|
wolffd@0
|
60 MEU
|
|
wolffd@0
|
61 end
|
|
wolffd@0
|
62 MEU
|
|
wolffd@0
|
63
|
|
wolffd@0
|
64 for e=exact(:)'
|
|
wolffd@0
|
65 assert(approxeq(MEU(e), 22.5))
|
|
wolffd@0
|
66 % U(T=yes) U(T=no)
|
|
wolffd@0
|
67 % 1 0
|
|
wolffd@0
|
68 assert(argmax(strategy{e}{T}) == 1); % test = yes
|
|
wolffd@0
|
69 t = 1; % test = yes
|
|
wolffd@0
|
70 % strategy{D} T R U(D=yes=1) U(D=no=2)
|
|
wolffd@0
|
71 % 1=yes 1=noS 0 1 Don't drill
|
|
wolffd@0
|
72 % 2=no 1=noS 1 0
|
|
wolffd@0
|
73 % 1=yes 2=opS 1 0
|
|
wolffd@0
|
74 % 2=no 2=opS 1 0
|
|
wolffd@0
|
75 % 1=yes 3=clS 1 0
|
|
wolffd@0
|
76 % 2=no 3=clS 1 0
|
|
wolffd@0
|
77 % 1=yes 4=unk 1 0
|
|
wolffd@0
|
78 % 2=no 4=unk 1 0
|
|
wolffd@0
|
79
|
|
wolffd@0
|
80 for r=[2 3] % OpS, ClS
|
|
wolffd@0
|
81 assert(argmax(squeeze(strategy{e}{D}(t,r,:))) == 1); % drill = yes
|
|
wolffd@0
|
82 end
|
|
wolffd@0
|
83 r = 1; % noS
|
|
wolffd@0
|
84 assert(argmax(squeeze(strategy{e}{D}(t,r,:))) == 2); % drill = no
|
|
wolffd@0
|
85 end
|
|
wolffd@0
|
86
|
|
wolffd@0
|
87
|
|
wolffd@0
|
88 for e=approx(:)'
|
|
wolffd@0
|
89 approxeq(strategy{exact(1)}{T}, strategy{e}{T})
|
|
wolffd@0
|
90 approxeq(strategy{exact(1)}{D}, strategy{e}{D})
|
|
wolffd@0
|
91 end
|
