Expert System. Knowledge-Based Systems. Page 1. Development of KB Systems. Knowledge base. Expert system = Structured computer program

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1 Knowlg-Bs Systms Exprt Systm Anrw Kusik 2139 Smns Cntr Iow City, Iow Tl: Fx: Knowlg s Infrn Engin Dt Exprt systm = Strutur omputr progrm Dvlopmnt of KB Systms Knowlg-Bs Systm Usr Tool uilr Domin xprt Usr intrf moul ES Shll KB systm uiling tool Knowlg nginr KB systm Clril Stff En-usr Knowlg s Infrn ngin Knowlgquisition moul Working mmory DM Softwr Exprts Pg 1 1

2 Knowlg Rprsnttion Mthos First-orr logi Proution ruls (inluing strutur proution ruls) Frms Smnti ntworks IF (onitions) THEN (onlusions) EXAMPLE IF Proution Ruls prt Pi is to ispth to mhin M tht is oupi y nothr prt Pj THEN hk vilility of n ltrntiv mhin M Avntgs of Proution Ruls Bsi Rsoning Strtgis Th us of rul n sily xplin to th systm usr Dvloprs n usrs n moify som ruls without rking th ntir systm Nw knowlg n inorport into th systm simply y ing nw ruls without onrn of how thy fit into th ovrll knowlg s Exmpl Ruls Bs: Forwr rsoning Bkwr rsoning R1: IF THEN Gol R2: IF THEN R3: IF THEN Pg 2 2

3 R1: IF THEN Gol Infrn (An/OR) tr IF sussmly sussmly r vill THEN initit th ssmly pross Gol R2: IF THEN IF prt prt hv n ssml THEN sussmly is vill Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol R1: IF THEN Gol R2: IF THEN R3: IF THEN R3: IF sunny, THEN hot insi R2: IF hot insi humi, THEN us AC R1: IF us AC mny popl, THEN swith on unit 2 Gol Givn th fts:,, n, riv gol Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Forwr Rsoning Gol R1 fir R2 fir R3 fir Infrn tr Pg 3 3

4 Givn th gol, riv fts tht prov it Bkwr Rsoning Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol R1 is stisfi, whil is not R3 R2 is stisfi, whil is not Forwr rsoning Bkwr rsoning Ruls: R1: IF THEN Gol R2: IF THEN R3: IF THEN Gol Infrn irtion Rsoning Summry Top-own infrn (Bkwr rsoning) n Infrn irtion is tru, is stisfi; thn th gol is stisfi Bottom-up infrn (Forwr rsoning) Unrtinty in Rul Bss Rul R1: IF A1 B1 THEN D1 Givn rtinty ftors: CF(A1) = CA1 CF(B1) = CB1 Th rtinty ftor of rul R1 CF(D1) = CF(R1) = CF(A1 B1) = min{cf(a1), CF(B1)} = min{ca1, CB2} Rul R2: IF A2 OR B2 Th rtinty ftor of Rul R2 THEN D2 CF(D2) = CF(R2) = CF(A2 OR B2) = mx{cf(a2), CF(B2)} = mx{ca2, CB2} Pg 4 4

5 C Rul R3: IF A1 B1 THEN D1 CF = R3.9 Crtinty ftor of R3 CF(D1) = CF(R3) = min{ca1, CB1} /OR tr with thr ruls A R B Rul R4: IF A2 OR B2 THEN D2 CF = Crtinty ftor of R4 CF(D2) = CF(R4) = mx{ca2, CB2} R1: IF F G THEN D R2: IF D E THEN A R3: IF A B THEN C D R E.8.9 F G Givn CF(F) =.8, CF(G) =.9, CF(E) =.95, n CF(B) =.75 n frtinty ftors of ruls R1, R2, n R3 CF(R1) =.85, CF(R2) =.9, n CF(R3) =.9 Dtrmin Crtinty ftors of D, A, n C CF(D) = min{cf(f), CF(G)}. CF(R1) =.6800 CF(A) = min{cf(d), CF(E)}. CF(R2) =.6120 CF(C) = min{cf(a), CF(B)}. CF(R3) =.5508 F D R A R2 G.9 C R E.75 B Givn two proution ruls n th orrsponing rtinty ftors: Rul R1: IF A1 B1 THEN D CF = 1 Rul R2: IF A2 OR B2 THEN D CF = 2 Rliility nlogy Th omin vin CF(R1, R2) = * 2 = 1 + 2(1-1) r1 r2 Pg 5 5

6 EXAMPLE: Comin Evin Rul R1: IF th infltion rt is lss thn 5% THEN stok mrkt pris go up CF = 1 = 0.7 Rul R2: IF unmploymnt rt is lss thn 7% THEN stok mrkt pris go up CF = 2 = 0.6 Th omin vin is omput s follows: KNOWLEDGE ACQUISITION METHODS KB systm intrfs Protool nlysis Nurl ntworks Dt mining CF(R1, R2) = * 2 = = 0.88 Pg 6 6

Knowledge-Based Systems. Outline 1. Outline 2. Expert System. Page 1. Development of KB Systems. CI = Computational Intelligence.

Knowledge-Based Systems. Outline 1. Outline 2. Expert System. Page 1. Development of KB Systems. CI = Computational Intelligence. Knowldg-Bsd Systms Andrw Kusik, Profssor 9 Smns Cntr Iow City, Iow - 7 ndrw-kusik@uiow.du http://www.in.uiow.du/~nkusik Tl: 9-9 Fx: 9-9 Outlin INTRODUCTION KNOWLEDGE REPRESENTATION - First-Ordr Logi -