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Qualitative Methods for Reasoning under Uncertainty 🔍
Simon D. Parsons The MIT Press, MIT Press, Cambridge, Mass, 2001
English [en] · PDF · 5.4MB · 2001 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/zlib · Save
description
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 abstractions such as interval values and information about how values change. The author does not invent completely new methods for reasoning under uncertainty but provides the means to create qualitative versions of existing methods. To illustrate this, he develops qualitative versions of probability theory, possibility theory, and the Dempster-Shafer theory of evidence.According to Parsons, these theories are best considered complementary rather than exclusive. Thus the book supports the contention that rather than search for the one best method to handle all imperfect information, one should use whichever method best fits the problem. This approach leads naturally to the use of several different methods in the solution of a single problem and to the complexity of integrating the results--a problem to which qualitative methods provide a solution.
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lgli/Qualitative Methods for Reasoning under Uncertainty.pdf
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lgrsnf/Qualitative Methods for Reasoning under Uncertainty.pdf
Alternative filename
zlib/Computers/Computer Science/Simon Parsons/Qualitative Methods for Reasoning under Uncertainty_2074162.pdf
Alternative title
Qualitative approaches for reasoning under uncertainty
Alternative author
Parsons, Simon
Alternative publisher
Ebsco Publishing
Alternative publisher
AAAI Press
Alternative edition
Artificial Intelligence Ser, Cambridge, Mass, ©2001
Alternative edition
Place of publication not identified, 2001
Alternative edition
United States, United States of America
Alternative edition
August 1, 2001
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0
metadata comments
lg919898
metadata comments
{"isbns":["0262161680","0585490228","9780262161688","9780585490229"],"last_page":509,"publisher":"MIT"}
Alternative description
2 All About Uncertainty 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 -- 3 Quantitative Methods For Reasoning With Imperfect Information 37 -- 3.2 Main Models 39 -- 3.3 Other Important Models 65 -- 3.4 Computational Techniques 73 -- 3.5 Quantified Logics 97 -- 4 Qualitative Methods For Reasoning With Imperfect Information 107 -- 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 -- 5 A Framework For Studying Different Methods 169 -- 5.2 Eclecticism And The Integration Problem 172 -- 5.3 A General Framework 184 -- 5.4 Examples Of Integration And Incompleteness 191 -- 6 Using Qualitative Algebras 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 -- 7 Theory Of Qualitative Change 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 -- 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 -- 9 Implementing The Qualitative Approaches 329 -- 9.2 Implementing Qualitative Algebras 330 -- 9.3 Implementing The Theory Of Qualitative Change 336 -- 10 Qualitative Protein Topology Prediction 353 -- 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 -- Appendix A Proofs Of Theorems 401 -- Appendix B Conditional Belief Calculations 445. Simon Parsons. Includes Bibliographical References (p. [457]-497) And Index.
Alternative description
Using qualitative methods to deal with imperfect information.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 abstractions such as interval values and information about how values change. The author does not invent completely new methods for reasoning under uncertainty but provides the means to create qualitative versions of existing methods. To illustrate this, he develops qualitative versions of probability theory, possibility theory, and the Dempster-Shafer theory of evidence.According to Parsons, these theories are best considered complementary rather than exclusive. Thus the book supports the contention that rather than search for the one best method to handle all imperfect information, one should use whichever method best fits the problem. This approach leads naturally to the use of several different methods in the solution of a single problem and to the complexity of integrating the results problem to which qualitative methods provide a solution.
Alternative description
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 abstractions such as interval values and information about how values change. The author does not invent completely new methods for reasoning under uncertainty but provides the means to create qualitative versions of existing methods. To illustrate this, he develops qualitative versions of probability theory, possibility theory, and the Dempster-Shafer theory of evidence. According to Parsons, these theories are best considered complementary rather than exclusive. Thus the book supports the contention that rather than search for the one best method to handle all imperfect information, one should use whichever method best fits the problem. This approach leads naturally to the use of several different methods in the solution of a single problem and to the complexity of integrating the results--a problem to which qualitative methods provide a solution
Alternative description
"Uncertainty" represents a wide variety of types of imperfect information. When working with uncertainties the author argues in favour of creating qualitative versions of existing methods and choosing the one that fits best
Alternative description
The discipline of artificial intelligence has as its aim the construction of computer-based systems that exhibit intelligence.
date open sourced
2013-05-14
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