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تئوري يقين Certainty Theory Vali Derhami Yazd University, Computer Department

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Presentation on theme: "تئوري يقين Certainty Theory Vali Derhami Yazd University, Computer Department"— Presentation transcript:

1 تئوري يقين Certainty Theory Vali Derhami Yazd University, Computer Department

2 Author: Vali Derhami 2/10 مقدمه  ارائه شواهد نايقين -1<= CF<=1  ارائه قوانين نايقين IF E1 AND E2 … THEN H CF=a  استنتاج نايقين  تركيب شواهد از چند منبع : IF A AND B THEN Z CF=0.8 IF C AND D THEN Z CF=0.7 Commutative: عدم تاثير ترتيب تحريك قوانين در سطح اعتقاد نهايي Asymptotic: مجانبي : اگر شواهد به سمت بي نهايت بروند سطح اعتقاد نيز به 1 نزديك ميشود.  Net Belief: Measure of Belief (MB), Measure of disbelief (MD), CF (H)=MB(H)-MD(H)

3 Author: Vali Derhami 3/10 مقدمه ( ادامه )  CF Value Interpretation: Uncertain TermsCF Definitely not Almost certainly not-0.8 Probably not-0.6 Maybe not-0.4 Unknown-0.2 to 0.2 Maybe0.4 Probably0.6 Almost certainly0.8 Definitely1 IF E Then H CF (Rules) CF(Rules)= CF (H, E) IF There are Dark clouds Then It will rain CF=0.8

4 Author: Vali Derhami 4/10 انتشار درجه يقين  Single Premise Rule: CF(H,E)=CF(E)*CF(RULE).  Conjunctive Rules: CF(H, E1 AND E2 AND..Ek)=min(CF(Ei)) *CF(RULE)  Disjunctive Rules: CF(H, E1 OR E2 OR..Ek)=Max(CF(Ei)) *CF(RULE)  Similarity Concludes Rules: Commutative Asymptotic CF1 + CF2-CF1* CF2 CF1, CF2 > 0 CF Combined = CF1 + CF2+ CF1*CF2 CF1, CF2 < 0 (CF1 + CF2 )/(1- min{|CF1 |,| CF2|}) CF1.CF2 < 0

5 Author: Vali Derhami 5/10 مثال 1-IF E1 OR E2 THEN H1 CF1=0.9 2-IF E3 THEN E1 CF2= IF E3 AND E4 THEN E2 CF3=0.9 4-IF E4 THEN E1 CF4=0.7 5-IF E1 THEN E2 CF5=0.95 Goal is H1 Backward chaining approach CF(E3)=0.95, CF(E4)=0.85

6 Author: Vali Derhami 6/10 Step 1: Rule1 is goal rule. Rule 2 and Rule 4 are subgoals Pursue Rule 2: ASK from user about E3 CF(E3)=0.95 Fire Rule 2: CF(E1,E3)= CF(E3)*CF (RULE2)=0.95*0.8=0.76 Pursue Rule 4: ASK from user about E4 CF(E4)=0.85 Fire Rule 4: CF(E1,E4)= CF(E4)*CF (RULE4)=0.85*0.7=0.6 CF(E1)=CF(E1,E3)+CF(E1,E4)- CF(E1,E3)* CF(E1,E4)= *0.6= 0.9 Rule 3 and 5 are subgols Rule 5 pursue: FIRE Rule 5: CF(E2,E1)=CF(E1)*CF(RULE 5)=0.9*0.95=0.85 Pursue Rule 3: Fire The rule: CF(E2, E3 And E4)=min (Cf(E3)CF(E4)*CF(Rule3)=min( )*0.9=0.76 CF(E2)=CF(E2,E3and E4)+CF(E2,E1)- CF(E2,E3AND E4)* CF(E2,E1)= *0.85=0.96 Fire Goal rule (Rule1): CF(H,E1 OR E2)=Max(Cf(E1), Cf(e2)) *Cf(Rule1)=max(0.9,0.96)*0.9=0.86 H:I should not go to the ballgame ES: I almost certainly should not go to theballgame

7 Author: Vali Derhami 7/10  E3 Cf (0.95)  CF(E1,E3) =0.76  CF(E4)=0.85  CF(E1,E4) =0.6  CF(E1)=0.9  CF(E2,E1)=0.85  CF(E2, E3 And E4)=0.76  CF(E2)=0.96  Cf(H,E1orE2)=0.86

8 Author: Vali Derhami 8/10  جستجوي ابتكاري (Heuristic Search) هرگاه از طريق چند قانون بتوان يك هدف را ثابت كرد،از قانون هاي با درجه يقين بالاتر شروع مي كنيم.  كنترل جستجو با درجه يقين استفاده از ابر قاعده IF CF( Problem is electrical system) < 0.5 Then GOAL=problem is fuel system  هرس كردن جستجو تعريف حد آستانه براي مثال MYCIN وقتي بين دو دهم و منهاي دو دهم قرار بگيرد ان هدف را کنار ميگذارد  پرسيدن CF از كاربر : بهتر است بصورت رشته ايي ( كيفي ) پرسيده شود تا عددي  OAVs and CF Assign each value a CF number

9 Author: Vali Derhami 9/10  متمايز كردن موارد نايقين مثال زير در LEVEL5 CONFIDENCE darkness of the sky  كسب درجه يقين از خبره Obtain the CF values from the expert ’ s use of qualified terms Don ’ t directly ask the expert for the CF values Use a transcription of a tape recording of a discussion with the expert to obtain the CF values  مرتب سازي اعتقادات فرضيه بر اساس CF: Problem CF Faulty carburetor 0.87 Clogged fuel filter 0.75 Bad Fuel 0.55

10 Author: Vali Derhami 10/10  مشكل زنجيره استنتاج عميق از زنجيره استنتاج عميق دوري كنيد  مشكل با تعداد زياد قوانين با تالي مشترك بخاطر ويژگي Asymptotic از نوشتن تعداد قوانين زياد با تالي مشترك دوري كنيد  مشكلات با قوانين داراي گزاره هاي مقدم AND شده


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