Expert Systems Principles and Programming

preface
foreword to the first edition
crapter 1: introdcion to expert systems

1.1 introduction

1.2 what is an expert system?

1.3 advantages of expert systems

1.4 general concepts of expert systems

1.5 characteristics of an expert system

1.6 the development of expert systems technology

1.7 expert systems applications and domains

1.8 languages, shells, and tools

1.9 elements of an expert system

1.10 production systems

1.11 procedural paradigms

1.12 nonprocedural paradigms

1.13 artificial neural systems

1.14 connectionist expert systems and inductive learning

1.15 summary


chapter 2: the representation of knowledge

.2.1 introduction

2.2 the meaning of knowledge

2.3 productions

2.4 semantic nets

2.5 object-attribute-value triples

2.6 prolog and semantic nets

2.7 difficulties with semantic nets

2.8 schemata

2.9 frames

2.10 difficulties with frames

2.11 logic and sets

2.12 propositional logic

2.13 the first order predicate logic

2.14 the universal quantifier

2.15 the existential quantifier

2.16 quantifiers and sets

2.17 limitations of predicate logic

2.18 summary


chapter 3: methods of inference

3.1 introduction

3.2 tress, lattices, and graphs

3.3 state and problem spaces

3.4 and-or trees and goals

3.5 deductive logic and syllogisms

3.6 rules of inference

3.7 limitations of propositional logic

3.8 first order predicate logic

3.9 logic systems

3.10 resolution

3.11 resolution systems and deduction

3.12 shallow and causal reasoning

3.13 resolution and first order predicate logic

3.14 forward and backward chaining

3.16 metaknowledge

3.17 summary


chapter 4: reasoning under uncertainty

4.1 introduction

4.2 uncertainty

4.3 types of error

4.4 errors and induction

4.5 classical probability

4.6 experimental and subjective probabilities

4.7 compound probabilities

4.8 conditional probabilities

4.9 hypothetical reasoning and backward induction

4.10 temporal reasoning and markov chains

4.11 the odds of belief

4.12 sufficiency and necessity

4.13 uncertainty in inference chains

4.14 the combination of evidence

4.15 inference nets

4.16 the propagation of probabilities

4.17 summary


chapter 5: inexact reasoning

5.1 introduction

5.2 uncertainty and rules

5.3 certainty factors

5.4 dempster-shafer theory

5.5 approximate reasoning

5.6 the state of uncertainty

5.7 summary


chapter 6: design of expert systems

6.1 introduction

6.2 selecting the appropriate problem

6.3 stages in the development of an expert system

6.4 errors in development stages
6.5 software engineering and expert systems

6.6 the expert system life cycle

6.7 a detailed life cycle model

6.8 summary


chapter 7: introduction to clips

7.1 introduction

7.2 clips

7.3 notation

7.4 fields

7.5 entering and exiting clips

7.6 facts

7.7 adding and removing facts

7.8 modifying and duplicating facts

7.9 the watch command

7.10 the deffacts construct

7.11 the components of a rule

7.12 the agenda and execution

7.13 commands for manipulating constructs

7.14 the printout command

7.15 using multiple rules

7.16 the set-break command

7.17 loading and saving constructs

7.18 commenting constructs

7.19 summary


chapter 8: pattern matching

8.1 introduction

8.2 variables

8.3 multiple use of variables

8.4 fact addresses

8.5 single-field wildcards

8.6 blocks world

8.7 multifield wildcards and variables

8.8 field constraints

8.9 functions and expressions

8.10 summing values using rules

8.11 the bind function

8.12 i/o functions

8.13 summary


chapter 9: advanced pattern matching

9.1 introduction

9.2 the game of sticks

9.3 input techniques

9.4 predicate functions

9.5 the test conditional element

9.6 the predicate field constraint

9.7 the return value field constraint

9.8 the sticks program

9.9 the or conditional element

9.10 the and conditional element

9.11 the not conditional element

9.12 the exists conditional element

9.13 the forall conditional element

9.14 the logical conditional element

9.15 utility commands

9.16 summary


chapter 10: modular design and execution control

10.1 introduction

10.2 deftemplate attributes

10.3 salience

10.4 phases and control facts

10.5 misuse of salience

10.6 the defmodule construct

10.7 importing and exporting facts

10.8 modules and execution control

10.9 summary


chapter 11: efficienlcy in rule-based languages

11.1 introduction

11.2 the rete pattern-matching algorithm

11.3 the pattern network

11.4 the join network

11.5 the importance of pattern order

11.6 ordering patterns for efficiency

11.7 multifield variables and efficiency

11.8 the test ce and efficiency

11.9 built-in pattern-matching constraints

11.10 general rules versus specific rules

11.11 procedural functions

11.12 simple rules versus complex rules

11.13 loading and saving farts

11.14 summary


chapter 12: expert system design examples

12.1 introduction

12.2 certainty factors

12.3 decision trees

12.4 backward chaining

12.5 a monitoring problem

12.6 summary


appendix a: some useful equivalences

appendix b: some elementary quantifiers

and their meanings

appendix c: some set properties

appendix d: clips support information

appendix e: clips command and function summary

appendix f: clips bnf

index