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Why is it snowing? EMYCIN solves our daily problems.

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Presentation on theme: "Why is it snowing? EMYCIN solves our daily problems."— Presentation transcript:

1 Why is it snowing? EMYCIN solves our daily problems

2 Description 1.If someone often wears shorts and sandals, then there is a good chance (.9) that they will cause snow. 2.If someone often wears shorts and thinks the weather is nice then there is a good chance (.7) that they will plan a barbeque. 3.If someone plans a barbeque and puts their winter jacket away then there is a good chance (.8) that they will cause snow. 4.If someone plans a barbeque and seldom wears shorts there is a good chance (.8) that they will not cause snow.

3 Rules (e1) wearsSandals(X, often)  wearsShorts(X, often)  1 causes(X, snow) –I(e1)=.9 (e2) wearsShorts(X, often)  thinksWeather(X, nice)  2 plans(X, barbeque) –I(e2)=.7 (e3) plans(X, barbeque)  putsAwayJacket(X, likely)  3 causes(X, snow) –I(e3)=.8 (e4) plans(X, barbeque)  wearsShorts(X, Seldom)  4  causes(X, snow) I(wearsSandals(Bob, often))=.6 I(wearsShorts(Bob, often))=.8 I(thinksWeather(Bob, nice))=.9 I(putsAwayJaxket(Bob, likely))=.8 I(wearsShorts(Bob, seldom)) =.2

4 What to do? We want to know if Bob causes snow –causes(Bob, snow) –So we need to know the Measure of Belief (MB) and the Measure of Disbelief (MD) –To calcualte both of these we need to know the MB and MD of plans(Bob, barbeque) to calculate I(plans(Bob, barbeque))

5 Barbeque MD(plans(Bob, barbeque)) –In this case no rules produce  plans(Bob, barbeque) MB(plans(Bob, barbeque)) –MB(plans(Bob, barbeque), e) = MB(plans(Bob, barbeque), {e2}) = I({e2}) * max(0, min(I(wearsShorts(Bob, often)), I(thinksWeather(Bob, nice)))) =.7 * max(0, min(.8,.7)) =.7 *.7 =.49 I(plans(Bob, barbeque)) = MB – MD =.49 – 0 =.49

6 causes(Bob, Snow) MD –MD(causes(Bob, snow), e) = MD(causes(Bob, snow), {e4}) = I({e4}) * max(0, min(I(plans(Bob, barbeque)), I(wearsShorts(Bob, seldom)))) =.8 * max(0, min(.49,.2)) = 0.16

7 causes(Bob, Snow) MB –MB(causes(Bob, Snow), {e1}) = I({e1}) * max(O, min(I(wearsSandals(Bob, often)), I(wearsShorts(Bob, often)))) =.9 * max(0, (.6,.8) =.54 –MB(causes(Bob, Snow), {e3}) = I({e3}) * max(0, min(I(plans(Bob, barbeque)), I(putsAwayJacket(Bob, likely)))) =.8 * max(0, min(.49,.54)) =.39

8 causes(Bob, Snow) MB(causes(Bob, snow), {e1, e3}) = MB(causes(Bob, snow), {e1} + MB(causes(Bob, snow), {e3})*(1- MB(causes(Bob, snow), {e1})) = *.46 =.77

9 I(causes(Bob, Snow) I(causes(Bob, Snow)) = MB – MD = =.61


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