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تئوري يقين Certainty Theory

تئوري يقين Certainty Theory . Vali Derhami Yazd University, Computer Department vderhami@yazduni.ac.ir. 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

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تئوري يقين Certainty Theory

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  1. تئوري يقين Certainty Theory Vali Derhami Yazd University, Computer Department vderhami@yazduni.ac.ir

  2. 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. مقدمه (ادامه) • CF Value Interpretation: IF E Then H CF (Rules) CF(Rules)= CF (H, E) IF There are Dark clouds Then It will rain CF=0.8

  4. 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 CFCombined = CF1+ CF2+ CF1*CF2 CF1, CF2 < 0 (CF1+ CF2)/(1- min{|CF1|,| CF2|}) CF1.CF2 < 0

  5. مثال 1-IF E1 OR E2 THEN H1 CF1=0.9 2-IF E3 THEN E1 CF2=0.8 3- 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. 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)=0.76+0.6-0.76*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(0.95.0.85)*0.9=0.76 CF(E2)=CF(E2,E3and E4)+CF(E2,E1)- CF(E2,E3AND E4)* CF(E2,E1)=0.76+0.85-0.76*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. 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. 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. 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. 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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