flex Expert System Toolkit - LPIS

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Appendix D - Dealing with Uncertainty 230 that the hypothesis is true. Absence of Evidence The absence of evidence is different from not knowing if the evidence is present or not, and can be used to reduce the probability of a hypothesis. The standard formula for updating the odds of a hypothesis, H, given that evidence, E, is absent is: O(H/~E) = D * O(H) where O(H/~E) is the odds of H given the absence of E, and D is the denies weigth of E. The definition of D is: D = P(~E/H) / P(~E/~H) or D = (1 - P(E/H)) / (1 - P(E/~H)) This is the ratio of probabilities that the evidence is not there when the hypothesis is true to when the hypothesis is false; i.e. given the evidence is absent, how likely is is that the hypothesis is true. Uncertain Evidence To refelect uncertainty in E, we scale both A and D to A’ and D’ respectively using linear interpolation. The expressions used to calculate interpolated values are: A’ = [2(A-1) * P(E)] + 2 - A D’ = [2(1-D) * P(E)] + D While P(E) is greater than 0.5 we use the affirms weigth, and when P(E) is less than 0.5, we use the denies weigth. <strong>flex</strong> toolkit
Appendix D - Dealing with Uncertainty 231 Certainty Theory Certainty theory, as used in MYCIN, represents an attempt to overcome some of the shortcomings of Bayesian updating. Instead of using probablities, each assertion has a certainty value between 1 and -1 associated with it, as do rules. The updating procedure for certainty values consists of adding a +ve or -ve value to the current certainty of a hypothesis. This contrasts with Bayesian updating where the odds of a hypothesis are always multiplied by the appropriate weighting. The basic formulae are: CF’ = CF’ x C(E) a) if C(H) >= 0 and CF’ >= 0 C(H/E) = C(H) + [CF’ x (1 - C(H))] b) if C(H)
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flex Reference By Dave Westwood
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The contents of this manual describ
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Contents 4 Contents Contents 4 1. I
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Contents 6 KSL Sentences 81 Frames
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Contents 8 Variant 196 Set 197 Gene
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1. Introduction 10 Forward Chaining
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2. Frames and Inheritance 12 2. Fra
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2. Frames and Inheritance 14 Defaul
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2. Frames and Inheritance 16 flex t
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2. Frames and Inheritance 18 define
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2. Frames and Inheritance 20 employ
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2. Frames and Inheritance 22 Inheri
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2. Frames and Inheritance 24 Depth-
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2. Frames and Inheritance 26 Univer
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2. Frames and Inheritance 28 The fl
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3. Forward Chaining 30 the axioms a
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3. Forward Chaining 32 flex toolkit
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3. Forward Chaining 34 A Simple Mod
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3. Forward Chaining 36 The basic cy
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3. Forward Chaining 38 First Come F
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3. Forward Chaining 40 considered.
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4. Data-Driven Programming 42 data-
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4. Data-Driven Programming 44 Const
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4. Data-Driven Programming 46 • c
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4. Data-Driven Programming 48 conte
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5. Questions And Answers 50 Rather
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5. Questions And Answers 52 Customi
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5. Questions And Answers 54 answer
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6. Anatomy of a flex Program 56 ?-
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6. Anatomy of a flex Program 58 fle
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6. Anatomy of a flex Program 60 and
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7. Knowledge Specification Language
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8. Run-Time Interpretation of KSL 1
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9. Flex Predicates 120 9. flex Tool
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9. Flex Predicates 122 ask( +Name )
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9. Flex Predicates 124 flex toolkit
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9. Flex Predicates 126 every_instan
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9. Flex Predicates 128 forward_chai
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9. Flex Predicates 130 Examples fle
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9. Flex Predicates 132 are : Search
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9. Flex Predicates 134 isa_demon( ?
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9. Flex Predicates 136 Example ?- i
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9. Flex Predicates 142 new_group( +
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9. Flex Predicates 144 one of the f
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9. Flex Predicates 146 new_synonym(
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9. Flex Predicates 148 the agenda.
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9. Flex Predicates 150 Examples rem
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9. Flex Predicates 152 remove_quest
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9. Flex Predicates 154 spied_chain
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9. Flex Predicates 156 If the exist
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11. Example - Robbie Goes Shopping
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Appendix A - Examples 166 Appendix
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tail Appendix A - Examples 168 herb
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Appendix A - Examples 170 Represent
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Appendix A - Examples 172 The Ident
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Appendix A - Examples 174 Example 2
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Appendix A - Examples 176 The Rules
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Appendix A - Examples 178 group sta
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Page 204 and 205: Appendix C - KSL Keyword Glossary 2
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Page 230 and 231: Appendix D - Dealing with Uncertain
Page 234 and 235: Index 232 — GENERAL INDEX — —
Page 236 and 237: Index 234 cycle, 111 cycle/3, 106 c
Page 238 and 239: Index 236 attribute of, 51 child, 7
Page 240 and 241: Index 238 isa_exception/1, 117 isa_
Page 242 and 243: Index 240 Ordering, 58, 59, 88, 105
Page 244 and 245: Index 242 create, 128 disabling of,
Page 246 and 247: Index 244 Updating agenda, 29, 74 U
Page 248 and 249: Index 246 false, 180, 193 first, 72
Page 250 and 251: Index 248 —flex PREDICATES INDEX
Page 252 and 253: Index 250 run_data/0, 137 run_data/
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