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1 % Evaluate effectiveness of likelihood weighting on the lawn sprinkler example
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2
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3 N = 4;
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4 dag = zeros(N,N);
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5 C = 1; R = 2; S = 3; W = 4;
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6 dag(C,[R S]) = 1;
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7 dag(R,W) = 1;
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8 dag(S,W)=1;
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9
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10 false = 1; true = 2;
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11 ns = 2*ones(1,N); % binary nodes
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12
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13 bnet = mk_bnet(dag, ns);
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14 bnet.CPD{C} = tabular_CPD(bnet, C, [0.5 0.5]);
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15 bnet.CPD{R} = tabular_CPD(bnet, R, [0.8 0.2 0.2 0.8]);
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16 bnet.CPD{S} = tabular_CPD(bnet, S, [0.5 0.9 0.5 0.1]);
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17 bnet.CPD{W} = tabular_CPD(bnet, W, [1 0.1 0.1 0.01 0 0.9 0.9 0.99]);
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18
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19
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20 clear engine;
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21 engine{1} = jtree_inf_engine(bnet);
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22 engine{2} = likelihood_weighting_inf_engine(bnet);
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23
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24 nengines = length(engine);
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25 m = cell(1, nengines);
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26 ll = zeros(1, nengines);
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27
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28 evidence = cell(1,N);
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29 %evidence{C} = true; % evidence at the top is the easiest
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30 evidence{W} = true; % evidence at the bottom is the hardets
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31
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32 query = [R];
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33
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34 i=1;
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35 engine{i} = enter_evidence(engine{i}, evidence);
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36 exact_m = marginal_nodes(engine{i}, query);
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37
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38 i=2;
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39 samples = 100:100:500;
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40 err = zeros(1, length(samples));
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41 for j=1:length(samples)
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42 nsamples = samples(j);
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43 engine{i} = enter_evidence(engine{i}, evidence, nsamples);
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44 approx_m = marginal_nodes(engine{i}, query);
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45 a1=approxeq(approx_m.T,exact_m.T,1e-1);
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46 a2=approxeq(approx_m.T,exact_m.T,1e-2);
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47 a3=approxeq(approx_m.T,exact_m.T,1e-3);
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48 e = sum(abs(approx_m.T(:) - exact_m.T(:)));
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49 fprintf('%d samples, 1dp %d, 2dp %d, 3dp %d, err %f\n', nsamples, a1, a2, a3, e);
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50 err(j) = e;
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51 end
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