Frontiers Of Expert Systems Book

	Preface	xi
1	Knowledge-Based Systems	1
1.1	Early Expert Systems	2
1.2	Roles, Tasks, Applications	4
1.3	Structure of an Expert System	5
1.4	Knowledge Representation	6
1.5	To use, or not to use?	7
1.6	Verification and Validation	10
1.7	The rest of this book	12
1.8	Bibliographic Notes	15
	Bibliography	17
2	Practical Reasoning	19
2.1	Formal Inference	20
2.1.1	Syntax	20
2.1.2	Inference Rules	21
2.1.3	Semantics	23
2.2	Temporal Logic	25
2.3	Non-Monotonic Reasoning	28
2.4	Truth Maintenance	31
2.5	Model Based Reasoning	33
2.6	Bibliographic Notes	35
	Bibliography	37
2.7	Exercises	39
3	Uncertainty	41
3.1	Probability	42
3.2	Likelihoods of Sufficiency and Necessity	45
3.3	Probabilistic Inference Networks	48
3.4	Interpolating Conditional Probabilities	51
3.5	Combining Evidence	55
3.6	Logical Inferences in Probabilistic Networks	60
3.7	Cycles and Multiple Dependencies	63
3.8	Reasoning in Acyclic Networks	66
3.9	Decision Theory and Utilities	75
3.9.1	Expected-Value Decision-Making	75
3.9.2	Utility Theory	78
3.10	Dempster-Shafer Calculus	82
3.10.1	Belief Mass	82
3.10.2	Combining Evidence	83
3.11	Fuzzy Systems	85
3.12	Certainty Factors	87
3.12	Bibliographic Notes	89
	Bibliography	91
3.14	Exercises	93
4	Rule Based Programming	99
4.1	Grammar Rules	100
4.2	Rewrite Rules	101
4.2.1	Petri Nets	102
4.3	Ordering the rules	103
4.4	Backward ho!	105
4.5	Production Rules	107
4.6	Inference Engine	113
4.7	Matching	114
4.8	Conflict Resolution	118
4.9	Specifying and Verifying Rules	120
4.9.1	Reasoning about actions	122
4.9.2	Nondeterminism	122
4.9.3	Variables	124
4.9.4	Priorities	124
4.10	Bibliographic Notes	125
	Bibliography	127
4.11	Exercises	129
5	Evolving Classifiers	133
5.1	Learning Classifier Systems	134
5.2	Representation	136
5.3	Rule Firing	138
5.4	Credit Allocation	140
5.5	Rule Discovery	143
5.6	Grouping Rules	145
5.7	Examples of Classifier Systems	147
5.8	Bibliographic Notes	150
	Bibliography	153
6	Connectionist Systems	157
6.1	Neural Networks	158
6.1.1	Node Functions	159
6.1.2	Network Architecture	160
6.1.3	Neural Learning	161
6.1.4	Connectionism and Expert Systems	163
6.2	KBCNN	163
6.3	MACIE	166
6.4	Bibliographic Notes	171
	Bibliography	173
6.5	Exercises	175
7	Case Based Reasoning Systems	177
7.1	Overview	178
7.2	Retrieval	180
7.3	Adaptation	183
7.3.1	Derivational Adaptation	184
7.3.2	Structural Adaptation	185
7.4	Case Library	186
7.4.1	Constructing the Case Library	187
7.4.2	Hierarchical Organization of Cases	188
7.5	Interfaces and Feedback	189
7.6	Case Based Learning	190
7.7	Examples	191
7.8	Analogical Reasoning	193
7.9	Bibliographic Notes	195
	Bibliography	197
7.10	Exercises	199
8	Knowledge Acquisition	201
8.1	Key Concerns	202
8.1.1	Hurdles	202
8.1.1.1	Language problems	202
8.1.1.2	Difficulty	203
8.1.1.3	Fallibility	203
8.1.1.4	Resistance	204
8.1.1.5	Interpretation	204
8.1.2	Procedure	205
8.2	Interacting with Experts	208
8.2.1	Unstructured Meetings	209
8.2.2	Nominal-Group Technique	209
8.2.3	Delphi Method	210
8.2.4	Blackboarding	210
8.2.5	Structured Interviews	210
8.2.6	Case Studies	211
8.2.6.1	Retrospective Case Study	211
8.2.6.2	Observational Case Study	212
8.2.7	Combining Different Techniques	212
8.3	Personal Construct Technology	212
8.3.1	Grid Analysis	213
8.3.2	Logic of Confirmation	217
8.3.3	Rule Generation Procedure	218
8.4	Induction of Knowledge	219
8.4.1	Splitting	221
8.4.2	Multi-class problems	227
8.4.3	Termination condition	227
8.4.4	Multivalued attributes	228
8.4.5	Computational Cost	229
8.4.6	Guidelines for Inductive Learning	229
8.5	Bibliographic Notes	231
	Bibliography	233
8.6	Exercises	235
9	Data Mining	237
9.1	Preprocessing	238
9.1.1	Overall Statistics	238
9.1.2	Noise	239
9.1.3	Missing Values	240
9.2	Transforming Representations	241
9.2.1	Normalization	241
9.2.2	Dimensionality Reduction	241
9.2.3	Data Reduction	242
9.3	Knowledge Discovery	244
9.3.1	Classification Trees	245
9.3.2	Clustering	245
9.3.3	Association Rules	247
9.4	Prediction	252
9.5	Bibliographic Notes	254
	Bibliography	255
10	Distributed Experts	259
10.1	Distributed Artificial Intelligence	260
10.2	Blackboard Systems	263
10.2.1	Hearsay	265
10.2.2	HASP	270
10.2.3	GBB	271
10.2.4	DVMT	272
10.2.5	BB1	273
10.3	Multiagent Systems	274
10.3.1	MAS Architectures	275
10.4	Agent Interactions	278
10.4.1	KQML	278
10.4.2	Agent coordination protocols	283
10.4.3	Cooperation protocols	285
10.4.4	Negotiation	287
10.5	Example Applications	288
10.5.1	Sensor Net	288
10.5.2	Emergency Management	289
10.5.3	Traffic Management	289
10.6	Bibliographic Notes	290
	Bibliography	291
10.7	Exercises	294
	Index	297