Multistrategy learning and theory revision

This article presents the system WHY, which learns and updates a diagnostic knowledge base using domain knowledge and a set of examples. The a priori knowledge consists of a causal model of the domain that states the relationships among basic phenomena, and a body of phenomenological theory that describes the links between abstract concepts and their possible manifestations in the world. The phenomenological knowledge is used deductively, the causal model is used abductively, and the examples are used inductively. The problems of imperfection and intractability of the theory are handled by allowing the system to make assumptions during its reasoning. In this way, robust knowledge can be learned with limited complexity and a small number of examples. The system works in a first-order logic environment and has been applied in a real domain.

[1]  Jack Minker,et al.  Logic and Data Bases , 1978, Springer US.

[2]  Tom Michael Mitchell,et al.  Explanation-based generalization: A unifying view , 1986 .

[3]  Tom M. Mitchell,et al.  Generalization as Search , 2002 .

[4]  M MitchellTom,et al.  Explanation-Based Generalization , 1986 .

[5]  Michael J. Pazzani,et al.  Integrating Explanation-Based and Empirical Learning Methods in OCCAM , 1988, EWSL.

[6]  Francesco Bergadano,et al.  A Knowledge Intensive Approach to Concept Induction , 1988, ML Workshop.

[7]  Randall Davis,et al.  Diagnostic Reasoning Based on Structure and Behavior , 1984, Artif. Intell..

[8]  Gary S. Kahn.  On When Diagnostic Systems Want to Do without Causal Knowledge , 1984, ECAI.

[9]  ElizabethH. Clark,et al.  BEDSIDE REBREATHING TECHNIQUE FOR MEASURING CARBON-MONOXIDE UPTAKE BY THE LUNG , 1978, The Lancet.

[10]  Ryszard S. Michalski,et al.  A theory and methodology of inductive learning , 1993 .

[11]  Keith L. Clark,et al.  Negation as Failure , 1987, Logic and Data Bases.

[12]  Ivan Bratko,et al.  Learning Redundant Rules in Noisy Domains , 1988, ECAI.

[13]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[14]  Yves Kodratoff,et al.  Induction and the Organization of Knowledge , 1994 .

[15]  Marco Botta,et al.  Improving Knowledge-Based System Performance by Experience , 1988, EWSL.

[16]  L. Console,et al.  Diagnostic Problem Solving: Combining Heuristic, Approximate and Causal Reasoning , 1988 .

[17]  Philip T. Cox,et al.  General Diagnosis by Abductive Inference , 1987, SLP.

[18]  Haym Hirsh,et al.  Reasoning about Operationality for Explanation-Based Learning , 1988, ML.

[19]  Ryszard S. Michalski,et al.  Inferential Learning Theory as a Basis for Multistrategy Task-Adaptive Learning , 1991 .

[20]  Luc De Raedt,et al.  CLINT : a multi-strategy interactive concept-learner and theory revision system , 1991 .

[21]  B. Chandrasekaran,et al.  Deep versus compiled knowledge approaches to diagnostic problem-solving , 1999, Int. J. Hum. Comput. Stud..

[22]  Gheonrhe D. Tecuci.  Learning as Understanding the External World , 1991 .

[23]  Johan de Kleer,et al.  Theories of Causal Ordering , 1986, Artif. Intell..

[24]  B. Chandrasekaran,et al.  Deep versus Compiled Knowledge Approaches to Diagnostic Problem-Solving , 1982, Int. J. Man Mach. Stud..

[25]  Gerald DeJong,et al.  A brief overview of explanatory schema acquisition , 1986 .

[26]  Francesco Bergadano,et al.  Deduction in Top-Down Inductive Learning , 1989, ML.

[27]  Michael Lebowitz,et al.  Integrated Learning: Controlling Explanation , 1986, Cogn. Sci..

[28]  David Poole,et al.  Representing Knowledge for Logic-Based Diagnosis , 1988, FGCS.

[29]  Michael R. Genesereth,et al.  The Use of Design Descriptions in Automated Diagnosis , 1984, Artif. Intell..

[30]  Richard M. Keller,et al.  Defining Operationality for Explanation-Based Learning , 1987, Artificial Intelligence.

[31]  Cristina Baroglio,et al.  Why: a system that learns using causal models and examples , 1994 .

[32]  R. Mooney,et al.  Explanation-Based Learning: An Alternative View , 1986, Machine Learning.

[33]  R. Mooney,et al.  A Multistrategy Approach to Theory Refinement , 1997 .

[34]  Alberto Maria Segre.  On the Operationality/Generality Trade-off in Explanation-based Learning , 1987, IJCAI.

[35]  A. Giordana,et al.  ENIGMA: A System That Learns Diagnostic Knowledge , 1993, IEEE Trans. Knowl. Data Eng..

[36]  Lorenza Saitta,et al.  Automated Concept Acquisition in Noisy Environments , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.