Qualitative methods for reasoning under uncertainty /
In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information. Instead, they work with...
Clasificación: | Libro Electrónico |
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Autor principal: | |
Formato: | Electrónico eBook |
Idioma: | Inglés |
Publicado: |
Cambridge, Mass. :
MIT Press,
©2001.
©2001 |
Colección: | Artificial Intelligence Ser.
|
Temas: | |
Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Machine generated contents note: 1 Introduction 1
- 2 All about uncertainty 7
- 2.1 Introduction 7
- 2.2 Taxonomies of uncertainty 9
- 2.3 Sources of imperfect information 15
- 2.4 Uncertainty and entropy 18
- 2.5 Human reasoning under uncertainty 20
- 2.6 Ground rules for formal systems 29
- 2.7 Summary 34
- 3 Quantitative methods for reasoning with imperfect information 37
- 3.1 Introduction 38
- 3.2 The main models 39
- 3.3 Other important models 65
- 3.4 Computational techniques 73
- 3.5 Quantified logics 97
- 3.6 Summary 105
- 4 Qualitative methods for reasoning with imperfect information 107
- 4.1 Introduction 108
- 4.2 Qualitative physics 109
- 4.3 Interval-based systems 117
- 4.4 Abstractions of quantitative systems 123
- 4.5 Defeasible reasoning 134
- 4.6 Combining and relating formalisms 155
- 4.7 Summary 166
- 5 A framework for studying different methods 169
- 5.1 Introduction 169
- 5.2 Eclecticism and the integration problem 172
- 5.3 A general framework 184
- 5.4 Examples of integration and incompleteness 191
- 5.5 Summary 199
- 6 Using qualitative algebras 201
- 6.1 Introduction 201
- 6.2 An algebra with qualitative values 202
- 6.3 An algebra of interval values 209
- 6.4 Other qualitative algebras 219
- 6.5 An example of handling integration 221
- 6.6 An example of handling incompleteness 228
- 6.7 Summary 233
- 7 The theory of qualitative change 237
- 7.1 Introduction 237
- 7.2 Basic concepts of qualitative change 239
- 7.3 Causal reasoning 247
- 7.4 Evidential reasoning 263
- 7.5 Handling incompleteness and integration 273
- 7.6 Summary 280
- 8 Further results in the theory of qualitative change 283
- 8.1 Synergy 283
- 8.2 Propagation in multiply-connected networks 296
- 8.3 Intercausal reasoning 311
- 8.4 Related work 322
- 8.5 Summary 327
- 9 Implementing the qualitative approaches 329
- 9.1 Introduction 330
- 9.2 Implementing qualitative algebras 330
- 9.3 Implementing the theory of qualitative change 336
- 9.4 Summary 351
- 10 Qualitative protein topology prediction 353
- 10.1 Introduction 354
- 10.2 Protein topology prediction 356
- 10.3 A first approach to modelling the uncertainty 358
- 10.4 A second approach to modeling the uncertainty 373
- 10.5 Discussion 387
- 10.6 Summary 389
- 11 Summary and conclusions 391
- 11.1 Summary 391
- 11.2 Conclusions 394.